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THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™ JULY/AUGUST 2012

VOLUME 5, NUMBER 5

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

EDITORIAL

“SCOTUS Redux” David B. Nash, MD, MBA COMMENTARY

Healthcare Reform After SCOTUS: Hard Decisions Needed to Avoid Health Sector Meltdown Joseph R. Antos, PhD ™

BUSINESS

Curbing the Costly Trend: Exploring the Need for a Progressive Approach to the Management of Specialty Pharmaceuticals Under the Medical Benefit Michael S. Jacobs, RPh; Kjel A. Johnson, PharmD, BCPS, FCCP, FAMCP Stakeholder Perspective by James T. Kenney, Jr, RPh, MBA CLINICAL

Anticoagulant Use for Prevention of Stroke in a Commercial Population with Atrial Fibrillation Aarti A. Patel, PharmD, MBA; Barb Lennert, RN, BSN, MAOM; Brian Macomson, PharmD; Winnie W. Nelson, PharmD; Gary M. Owens, MD; Samir H. Mody, PharmD, MBA; Jeff Schein, DrPH, MPH Stakeholder Perspective by Jack E. Fincham, PhD, RPh

Conceptual and Analytical Considerations toward the Use of Patient-Reported Outcomes in Personalized Medicine Demissie Alemayehu, PhD; Joseph C. Cappelleri, PhD, MPH Stakeholder Perspective by Michael F. Murphy, MD, PhD INDUSTRY TRENDS

Cost Management through Care Management: A Perspective on Choosing the Right Specialty Pharmacy Partner, PART 1 Michael Einodshofer, RPh, MBA; Stephen Kansler

©2012 Engage Healthcare Communications, LLC www.AHDBonline.com


R D IV O F AN D E US ION V O EO AT R P AN STR P A UT INI BC DM U S A

VELCADEHCP.COM


If you define value as an overall survival advantage: VELCADE® (bortezomib) DELIVERED A >13-MONTH OVERALL SURVIVAL ADVANTAGE At 5-year median follow-up, VELCADE (bortezomib)+MP* provided a median overall survival of 56.4 months vs 43.1 months with MP alone (HR=0.695 [95% CI, 0.57-085]; p<0.05)† At 3-year median follow-up, VELCADE+MP provided an overall survival advantage over MP that was not regained with subsequent therapies

If you define value as defined length of therapy: Results achieved using VELCADE twice-weekly followed by weekly dosing for a median of 50 weeks (54 planned)1

If you define value as medication cost: Medication cost is an important factor when considering overall drug spend. The Wholesale Acquisition Cost for VELCADE is $1,471 per 3.5-mg vial as of January 2012 Health plans should consider medication cost, length of therapy, and dosing regimens when determining the value of a prescription drug regimen. This list of considerations is not meant to be all-inclusive; there are multiple other factors to consider when determining value for a given regimen

VELCADE Indication and Important Safety Information INDICATION VELCADE is indicated for the treatment of patients with multiple myeloma.

CONTRAINDICATIONS VELCADE is contraindicated in patients with hypersensitivity to bortezomib, boron, or mannitol. VELCADE is contraindicated for intrathecal administration.

WARNINGS, PRECAUTIONS AND DRUG INTERACTIONS Peripheral neuropathy, including severe cases, may occur — manage with dose modification or discontinuation. Patients with preexisting severe neuropathy should be treated with VELCADE only after careful risk-benefit assessment Hypotension can occur. Use caution when treating patients receiving antihypertensives, those with a history of syncope, and those who are dehydrated Closely monitor patients with risk factors for, or existing heart disease Acute diffuse infiltrative pulmonary disease has been reported Nausea, diarrhea, constipation, and vomiting have occurred and may require use of antiemetic and antidiarrheal medications or fluid replacement Thrombocytopenia or neutropenia can occur; complete blood counts should be regularly monitored throughout treatment Tumor Lysis Syndrome, Reversible Posterior Leukoencephalopathy Syndrome, and Acute Hepatic Failure have been reported Women should avoid becoming pregnant while being treated with VELCADE. Pregnant women should be apprised of the potential harm to the fetus Closely monitor patients receiving VELCADE in combination with strong CYP3A4 inhibitors. Concomitant use of strong CYP3A4 inducers is not recommended

ADVERSE REACTIONS Most commonly reported adverse reactions (incidence ≥30%) in clinical studies include asthenic conditions, diarrhea, nausea, constipation, peripheral neuropathy, vomiting, pyrexia, thrombocytopenia, psychiatric disorders, anorexia and decreased appetite, neutropenia, neuralgia, leukopenia, and anemia. Other adverse reactions, including serious adverse reactions, have been reported Please see Brief Summary for VELCADE on the next page of this advertisement. To contact a reimbursement specialist: Please call 1-866-VELCADE, Option 2 (1-866-835-2233). *Melphalan+prednisone. † VISTA: a randomized, open-label, international phase 3 trial (N=682) evaluating the efficacy and safety of VELCADE administered intravenously in combination with MP vs MP in previously untreated multiple myeloma. The primary endpoint was TTP. Secondary endpoints were CR, ORR, PFS, and overall survival. At a pre-specified interim analysis (median follow-up 16.3 months), VELCADE+MP resulted in significantly superior results for TTP (median 20.7 months with VELCADE+MP vs 15.0 months with MP [p=0.000002]), PFS, overall survival, and ORR. Further enrollment was halted and patients receiving MP were offered VELCADE in addition. Updated analyses were performed. Reference: 1. Mateos M-V, Richardson PG, Schlag R, et al. Bortezomib plus melphalan and prednisone compared with melphalan and prednisone in previously untreated multiple myeloma: updated follow-up and impact of subsequent therapy in the phase III VISTA trial. J Clin Oncol. 2010;28(13):2259-2266.


Brief Summary INDICATIONS: VELCADE® (bortezomib) for Injection is indicated for the treatment of patients with multiple myeloma. VELCADE is indicated for the treatment of patients with mantle cell lymphoma who have received at least 1 prior therapy. CONTRAINDICATIONS: VELCADE is contraindicated in patients with hypersensitivity to bortezomib, boron, or mannitol. VELCADE is contraindicated for intrathecal administration. WARNINGS AND PRECAUTIONS: VELCADE should be administered under the supervision of a physician experienced in the use of antineoplastic therapy. Complete blood counts (CBC) should be monitored frequently during treatment with VELCADE. Peripheral Neuropathy: VELCADE treatment causes a peripheral neuropathy that is predominantly sensory. However, cases of severe sensory and motor peripheral neuropathy have been reported. Patients with pre-existing symptoms (numbness, pain or a burning feeling in the feet or hands) and/or signs of peripheral neuropathy may experience worsening peripheral neuropathy (including ≥ Grade 3) during treatment with VELCADE. Patients should be monitored for symptoms of neuropathy, such as a burning sensation, hyperesthesia, hypoesthesia, paresthesia, discomfort, neuropathic pain or weakness. In the Phase 3 relapsed multiple myeloma trial comparing VELCADE subcutaneous vs. intravenous the incidence of Grade ≥ 2 peripheral neuropathy events was 24% for subcutaneous and 41% for intravenous. Grade ≥ 3 peripheral neuropathy occurred in 6% of patients in the subcutaneous treatment group, compared with 16% in the intravenous treatment group. Starting VELCADE subcutaneously may be considered for patients with pre-existing or at high risk of peripheral neuropathy. Patients experiencing new or worsening peripheral neuropathy during VELCADE therapy may benefit from a decrease in the dose and/or a less dose-intense schedule. In the single agent phase 3 relapsed multiple myeloma study of VELCADE vs. Dexamethasone following dose adjustments, improvement in or resolution of peripheral neuropathy was reported in 51% of patients with ≥ Grade 2 peripheral neuropathy in the relapsed multiple myeloma study. Improvement in or resolution of peripheral neuropathy was reported in 73% of patients who discontinued due to Grade 2 neuropathy or who had ≥ Grade 3 peripheral neuropathy in the phase 2 multiple myeloma studies. The long-term outcome of peripheral neuropathy has not been studied in mantle cell lymphoma. Hypotension: The incidence of hypotension (postural, orthostatic, and hypotension NOS) was 13%. These events are observed throughout therapy. Caution should be used when treating patients with a history of syncope, patients receiving medications known to be associated with hypotension, and patients who are dehydrated. Management of orthostatic/postural hypotension may include adjustment of antihypertensive medications, hydration, and administration of mineralocorticoids and/or sympathomimetics. Cardiac Disorders: Acute development or exacerbation of congestive heart failure and new onset of decreased left ventricular ejection fraction have been reported, including reports in patients with no risk factors for decreased left ventricular ejection fraction. Patients with risk factors for, or existing heart disease should be closely monitored. In the relapsed multiple myeloma study of VELCADE vs. dexamethasone, the incidence of any treatment-emergent cardiac disorder was 15% and 13% in the VELCADE and dexamethasone groups, respectively. The incidence of heart failure events (acute pulmonary edema, cardiac failure, congestive cardiac failure, cardiogenic shock, pulmonary edema) was similar in the VELCADE and dexamethasone groups, 5% and 4%, respectively. There have been isolated cases of QT-interval prolongation in clinical studies; causality has not been established. Pulmonary Disorders: There have been reports of acute diffuse infiltrative pulmonary disease of unknown etiology such as pneumonitis, interstitial pneumonia, lung infiltration and Acute Respiratory Distress Syndrome (ARDS) in patients receiving VELCADE. Some of these events have been fatal. In a clinical trial, the first two patients given high-dose cytarabine (2 g/m2 per day) by continuous infusion with daunorubicin and VELCADE for relapsed acute myelogenous leukemia died of ARDS early in the course of therapy. There have been reports of pulmonary hypertension associated with VELCADE administration in the absence of left heart failure or significant pulmonary disease. In the event of new or worsening cardiopulmonary symptoms, a prompt comprehensive diagnostic evaluation should be conducted. Reversible Posterior Leukoencephalopathy Syndrome (RPLS): There have been reports of RPLS in patients receiving VELCADE. RPLS is a rare, reversible, neurological disorder which can present with seizure, hypertension, headache, lethargy, confusion, blindness, and other visual and neurological disturbances. Brain imaging, preferably MRI (Magnetic Resonance Imaging), is used to confirm the diagnosis. In patients developing RPLS, discontinue VELCADE. The safety of reinitiating VELCADE therapy in patients previously experiencing RPLS is not known. Gastrointestinal Adverse Events: VELCADE treatment can cause nausea, diarrhea, constipation, and vomiting sometimes requiring use of antiemetic and antidiarrheal medications. Ileus can occur. Fluid and electrolyte replacement should be administered to prevent dehydration. Thrombocytopenia/Neutropenia: VELCADE is associated with thrombocytopenia and neutropenia that follow a cyclical pattern with nadirs occurring following the last dose of each cycle and typically recovering prior to initiation of the subsequent cycle. The cyclical pattern of platelet and neutrophil decreases and recovery remained consistent over the 8 cycles of twice weekly dosing, and there was no evidence of cumulative thrombocytopenia or neutropenia. The mean platelet count nadir measured was approximately 40% of baseline. The severity of thrombocytopenia was related to pretreatment platelet count. In the relapsed multiple myeloma study of VELCADE vs. dexamethasone, the incidence of significant bleeding events (≥Grade 3) was similar on both the VELCADE (4%) and dexamethasone (5%) arms. Platelet counts should be monitored prior to each dose of VELCADE. Patients experiencing thrombocytopenia may require change in the dose and schedule of VELCADE. There have been reports of gastrointestinal and intracerebral hemorrhage in association with VELCADE. Transfusions may be considered. The incidence of febrile neutropenia was <1%. Tumor Lysis Syndrome: Because VELCADE is a cytotoxic agent and can rapidly kill malignant cells, the complications of tumor lysis syndrome may occur. Patients at risk of tumor lysis syndrome are those with high tumor burden prior to treatment. These patients should be monitored closely and appropriate precautions taken. Hepatic Events: Cases of acute liver failure have been reported in patients receiving multiple concomitant medications and with serious underlying medical conditions. Other reported hepatic events include increases in liver enzymes, hyperbilirubinemia, and hepatitis. Such changes may be reversible upon discontinuation of VELCADE. There is limited re-challenge information in these patients. Hepatic Impairment: Bortezomib is metabolized by liver enzymes. Bortezomib exposure is increased in patients with moderate or severe hepatic impairment; these patients should be treated with VELCADE at reduced starting doses and closely monitored for toxicities. Use in Pregnancy: Pregnancy Category D. Women of childbearing potential should avoid becoming pregnant while being treated with VELCADE. Bortezomib administered to rabbits during organogenesis at a dose approximately 0.5 times the clinical dose of 1.3 mg/m2 based on body surface area caused post-implantation loss and a decreased number of live fetuses.

ADVERSE EVENT DATA: Safety data from phase 2 and 3 studies of single-agent VELCADE (bortezomib) 1.3 mg/m2/dose administered intravenously twice weekly for 2 weeks followed by a 10-day rest period in 1163 patients with previously treated multiple myeloma (N=1008, not including the phase 3, VELCADE plus DOXIL® [doxorubicin HCI liposome injection] study) and previously treated mantle cell lymphoma (N=155) were integrated and tabulated. In these studies, the safety profile of VELCADE was similar in patients with multiple myeloma and mantle cell lymphoma. In the integrated analysis, the most commonly reported adverse events were asthenic conditions (including fatigue, malaise, and weakness); (64%), nausea (55%), diarrhea (52%), constipation (41%), peripheral neuropathy NEC (including peripheral sensory neuropathy and peripheral neuropathy aggravated); (39%), thrombocytopenia and appetite decreased (including anorexia); (each 36%), pyrexia (34%), vomiting (33%), anemia (29%), edema (23%), headache, paresthesia and dysesthesia (each 22%), dyspnea (21%), cough and insomnia (each 20%), rash (18%), arthralgia (17%), neutropenia and dizziness (excluding vertigo); (each 17%), pain in limb and abdominal pain (each 15%), bone pain (14%), back pain and hypotension (each 13%), herpes zoster, nasopharyngitis, upper respiratory tract infection, myalgia and pneumonia (each 12%), muscle cramps (11%), and dehydration and anxiety (each 10%). Twenty percent (20%) of patients experienced at least 1 episode of ≥Grade 4 toxicity, most commonly thrombocytopenia (5%) and neutropenia (3%). A total of 50% of patients experienced serious adverse events (SAEs) during the studies. The most commonly reported SAEs included pneumonia (7%), pyrexia (6%), diarrhea (5%), vomiting (4%), and nausea, dehydration, dyspnea and thrombocytopenia (each 3%). In the phase 3 VELCADE + melphalan and prednisone study in previously untreated multiple myeloma, the safety profile of VELCADE administered intravenously in combination with melphalan/prednisone is consistent with the known safety profiles of both VELCADE and melphalan/prednisone. The most commonly reported adverse events in this study (VELCADE+melphalan/prednisone vs melphalan/prednisone) were thrombocytopenia (52% vs 47%), neutropenia (49% vs 46%), nausea (48% vs 28%), peripheral neuropathy (47% vs 5%), diarrhea (46% vs 17%), anemia (43% vs 55%), constipation (37% vs 16%), neuralgia (36% vs 1%), leukopenia (33% vs 30%), vomiting (33% vs 16%), pyrexia (29% vs 19%), fatigue (29% vs 26%), lymphopenia (24% vs 17%), anorexia (23% vs 10%), asthenia (21% vs 18%), cough (21% vs 13%), insomnia (20% vs 13%), edema peripheral (20% vs 10%), rash (19% vs 7%), back pain (17% vs 18%), pneumonia (16% vs 11%), dizziness (16% vs 11%), dyspnea (15% vs 13%), headache (14% vs 10%), pain in extremity (14% vs 9%), abdominal pain (14% vs 7%), paresthesia (13% vs 4%), herpes zoster (13% vs 4%), bronchitis (13% vs 8%), hypokalemia (13% vs 7%), hypertension (13% vs 7%), abdominal pain upper (12% vs 9%), hypotension (12% vs 3%), dyspepsia (11% vs 7%), nasopharyngitis (11% vs 8%), bone pain (11% vs 10%), arthralgia (11% vs 15%) and pruritus (10% vs 5%). In the phase 3 VELCADE subcutaneous vs. intravenous study in relapsed multiple myeloma, safety data were similar between the two treatment groups. The most commonly reported adverse events in this study were peripheral neuropathy NEC (38% vs 53%), anemia (36% vs 35%), thrombocytopenia (35% vs 36%), neutropenia (29% vs 27%), diarrhea (24% vs 36%), neuralgia (24% vs 23%), leukopenia (20% vs 22%), pyrexia (19% vs 16%), nausea (18% vs 19%), asthenia (16% vs 19%), weight decreased (15% vs 3%), constipation (14% vs 15%), back pain (14% vs 11%), fatigue (12% vs 20%), vomiting (12% vs 16%), insomnia (12% vs 11%), herpes zoster (11% vs 9%), decreased appetite (10% vs 9%), hypertension (10% vs 4%), dyspnea (7% vs 12%), pain in extremities (5% vs 11%), abdominal pain and headache (each 3% vs 11%), abdominal pain upper (2% vs 11%). The incidence of serious adverse events was similar for the subcutaneous treatment group (36%) and the intravenous treatment group (35%). The most commonly reported SAEs were pneumonia (6%) and pyrexia (3%) in the subcutaneous treatment group and pneumonia (7%), diarrhea (4%), peripheral sensory neuropathy (3%) and renal failure (3%) in the intravenous treatment group. DRUG INTERACTIONS: Bortezomib is a substrate of cytochrome P450 enzyme 3A4, 2C19 and 1A2. Co-administration of ketoconazole, a strong CYP3A4 inhibitor, increased the exposure of bortezomib by 35% in 12 patients. Therefore, patients should be closely monitored when given bortezomib in combination with strong CYP3A4 inhibitors (e.g. ketoconazole, ritonavir). Co-administration of omeprazole, a strong inhibitor of CYP2C19, had no effect on the exposure of bortezomib in 17 patients. Co-administration of rifampin, a strong CYP3A4 inducer, is expected to decrease the exposure of bortezomib by at least 45%. Because the drug interaction study (n=6) was not designed to exert the maximum effect of rifampin on bortezomib PK, decreases greater than 45% may occur. Efficacy may be reduced when VELCADE is used in combination with strong CYP3A4 inducers; therefore, concomitant use of strong CYP3A4 inducers is not recommended in patients receiving VELCADE. St. John’s Wort (Hypericum perforatum) may decrease bortezomib exposure unpredictably and should be avoided. Co-administration of dexamethasone, a weak CYP3A4 inducer, had no effect on the exposure of bortezomib in 7 patients. Co-administration of melphalan-prednisone increased the exposure of bortezomib by 17% in 21 patients. However, this increase is unlikely to be clinically relevant. USE IN SPECIFIC POPULATIONS: Nursing Mothers: It is not known whether bortezomib is excreted in human milk. Because many drugs are excreted in human milk and because of the potential for serious adverse reactions in nursing infants from VELCADE, a decision should be made whether to discontinue nursing or to discontinue the drug, taking into account the importance of the drug to the mother. Pediatric Use: The safety and effectiveness of VELCADE in children has not been established. Geriatric Use: No overall differences in safety or effectiveness were observed between patients ≥age 65 and younger patients receiving VELCADE; but greater sensitivity of some older individuals cannot be ruled out. Patients with Renal Impairment: The pharmacokinetics of VELCADE are not influenced by the degree of renal impairment. Therefore, dosing adjustments of VELCADE are not necessary for patients with renal insufficiency. Since dialysis may reduce VELCADE concentrations, VELCADE should be administered after the dialysis procedure. For information concerning dosing of melphalan in patients with renal impairment, see manufacturer’s prescribing information. Patients with Hepatic Impairment: The exposure of bortezomib is increased in patients with moderate and severe hepatic impairment. Starting dose should be reduced in those patients. Patients with Diabetes: During clinical trials, hypoglycemia and hyperglycemia were reported in diabetic patients receiving oral hypoglycemics. Patients on oral antidiabetic agents receiving VELCADE treatment may require close monitoring of their blood glucose levels and adjustment of the dose of their antidiabetic medication. Please see full Prescribing Information for VELCADE at VELCADEHCP.com.

VELCADE, MILLENNIUM and are registered trademarks of Millennium Pharmaceuticals, Inc. Other trademarks are property of their respective owners. Millennium Pharmaceuticals, Inc., Cambridge, MA 02139 Copyright © 2012, Millennium Pharmaceuticals, Inc. All rights reserved. Printed in USA

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EDITORIAL BOARD EDITOR-IN-CHIEF

David B. Nash, MD, MBA Dean, the Dr Raymond C. and Doris N. Grandon Professor, Jefferson School of Population Health Philadelphia, PA DEPUTY EDITORS

Joseph D. Jackson, PhD Program Director, Applied Health Economics and Outcomes Research, Jefferson University School of Population Health, Philadelphia, PA Laura T. Pizzi, PharmD, MPH, RPh Associate Professor, Department of Pharmacy Practice, Jefferson School of Pharmacy Philadelphia, PA AGING AND WELLNESS

Eric G. Tangalos, MD, FACP, AGSF, CMD Professor of Medicine Mayo Clinic, Rochester, MN CANCER RESEARCH

Al B. Benson, III, MD, FACP Professor of Medicine, Associate Director for Clinical Investigations Robert H. Lurie Comprehensive Cancer Center Northwestern University, IL Past President, ACCC Past Chair, NCCN Board of Directors Samuel M. Silver, MD, PhD, FASCO Professor of Internal Medicine Hematology/Oncology Assistant Dean for Research Associate Director, Faculty Group Practice University of Michigan Medical School, MI Arthur F. Shinn, PharmD, FASCP President, Managed Pharmacy Consultants, LLC, Lake Worth, FL F. Randy Vogenberg, RPh, PhD Principal, Institute for Integrated Healthcare and Bentteligence, Sharon, MA ENDOCRINOLOGY RESEARCH

MANAGED MARKETS

James V. Felicetta, MD Chairman, Dept. of Medicine Carl T. Hayden Veterans Affairs Medical Center, Phoenix, AZ EPIDEMIOLOGY RESEARCH

Joshua N. Liberman, PhD Executive Director, Research, Development & Dissemination Sutter Health, Concord, CA GOVERNMENT

Kevin B. “Kip” Piper, MA, FACHE President, Health Results Group, LLC Washington, DC HEALTH INFORMATION TECHNOLOGY Kelly Huang, PhD President, HealthTronics, Inc. Austin, TX J. B. Jones, PhD, MBA Research Investigator, Geisinger Health System, Danville, PA Victor J. Strecher, PhD, MPH Professor and Director for Innovation and Social Entrepreneurship University of Michigan, School of Public Health and Medicine, Ann Arbor, MI HEALTH OUTCOMES RESEARCH

Diana Brixner, RPh, PhD Professor and Chair Department of Pharmacotherapy Executive Director, Outcomes Research Center, Director of Outcomes Personalized Health Care Program, University of Utah Salt Lake City, UT

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POLICY & PUBLIC HEALTH

HEALTH & VALUE PROMOTION

Craig Deligdish, MD Hematologist/Oncologist Oncology Resource Networks, Orlando, FL Thomas G. McCarter, MD, FACP Chief Clinical Officer Executive Health Resources, PA Albert Tzeel, MD, MHSA, FACPE National Medical Director HumanaOne, Waukesha, WI

EMPLOYERS

Teresa DeLuca, MD, MBA Senior VP, PBM Leader Humana Solutions, Louisville, KY Leslie S. Fish, PharmD Vice President of Clinical Programs Fallon Community Health Plan, MA John Hornberger, MD, MS Cedar Associates, LLC CHP/PCOR Adjunct Associate, Menlo Park, CA Michael S. Jacobs, RPh Vice President, National Accounts Truveris, Inc., New York, NY Matthew Mitchell, PharmD, MBA Manager, Pharmacy Services SelectHealth, Salt Lake City, UT Paul Anthony Polansky, BSPharm, MBA Senior Field Scientist, Health Outcomes and PharmacoEconomics (HOPE) Endo Health Solutions, Chadds Ford, PA Christina A. Stasiuk, DO, FACOI Senior Medical Director Cigna, Philadelphia, PA Scott R. Taylor, BSPharm, MBA Executive Director, Industry Relations Geisinger Health System, Danville, PA

Joseph Couto, PharmD, MBA Clinical Program Manager Cigna Corporation, Bloomfield, CT Steve Miff, PhD Senior Vice President VHA, Inc., Irving, TX Kavita V. Nair, PhD Associate Professor, School of Pharmacy University of Colorado at Denver, CO Gary M. Owens, MD President, Gary Owens Associates Glen Mills, PA Andrew M. Peterson, PharmD, PhD Dean, Mayes School of Healthcare Business and Policy, Associate Professor, University of the Sciences, Philadelphia, PA Sarah A. Priddy, PhD Director, Competitive Health Analytics Humana, Louisville, KY Timothy S. Regan, BPharm, RPh, CPh Executive Director, Strategic Accounts Xcenda, Palm Harbor, FL Vincent J. Willey, PharmD Associate Professor, Philadelphia School of Pharmacy, University of the Sciences Philadelphia, PA David W. Wright, MPH President, Institute for Interactive Patient Care Bethesda, MD

Jeffrey A. Bourret, RPh, MS, FASHP Senior Director, Medical Lead, Payer and Specialty Channel Strategy, Medical Affairs Pfizer Specialty Care Business Unit, PA Richard B. Weininger, MD Chairman, CareCore National, LLC Bluffton, SC PATIENT ADVOCACY

William E. Fassett, BSPharm, MBA, PhD, FAPhA Professor of Pharmacy Law & Ethics Dept. of Pharmacotherapy, College of Pharmacy Washington State University, Spokane, WA Mike Pucci Sr VP Commercial Operations and Business Development, PhytoChem Pharmaceuticals Lake Gaston, NC PERSONALIZED MEDICINE

Emma Kurnat-Thoma, PhD, MS, RN Director, Research Services URAC, Washington, DC PHARMACOECONOMICS

Josh Feldstein President & CEO CAVA, The Center for Applied Value Analysis, Inc., Norwalk, CT Jeff Jianfei Guo, BPharm, MS, PhD Professor of Pharmacoeconomics & Pharmacoepidemiology, College of Pharmacy, University of Cincinnati Medical Center, OH

RESEARCH & DEVELOPMENT

Frank Casty, MD, FACP Chief Medical Officer Senior VP, Clinical Development Medical Science Endo Pharmaceuticals, Chadds Ford, PA Michael F. Murphy, MD, PhD Chief Medical Officer and Scientific Officer Worldwide Clinical Trials King of Prussia, PA SPECIALTY PHARMACY

Atheer A. Kaddis, PharmD Senior Vice President Managed Markets/Clinical Services Diplomat Specialty Pharmacy Flint, MI James T. Kenney, Jr, RPh, MBA Pharmacy Operations Manager Harvard Pilgrim Health Care Wellesley, MA Michael Kleinrock Director, Research Development IMS Institute for Healthcare Informatics Collegeville, PA

PHARMACY BENEFIT DESIGN

Joel V. Brill, MD, AGAF, CHCQM Chief Medical Officer, Predictive Health, Phoenix, AZ

www.AHDBonline.com

Joseph R. Antos, PhD Wilson H. Taylor Scholar in Health Care Retirement Policy, American Enterprise Institute Washington, DC Robert W. Dubois, MD, PhD Chief Science Officer National Pharmaceutical Council, Washington, DC Jack E. Fincham, PhD, RPh Professor of Pharmacy, Practice and Administration School of Pharmacy, University of Missouri Kansas City, MO Walid F. Gellad, MD, MPH Assistant Professor of Medicine, University of Pittsburgh, Staff Physician, Pittsburgh VA Medical Center, Adjunct Scientist, RAND Health Paul Pomerantz, MBA Executive Director Drug Information Association, Horsham, PA J. Warren Salmon, PhD Professor of Health Policy & Administration School of Public Health University of Illinois at Chicago Raymond L. Singer, MD, MMM, CPE, FACS Chief, Division of Cardiothoracic Surgery Vice Chair, Department of Surgery for Quality & Patient Safety and Outreach Lehigh Valley Health Network, PA

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VOLUME 5, NUMBER 5

THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

TABLE OF CONTENTS

EDITORIAL

268 “SCOTUS Redux” David B. Nash, MD, MBA COMMENTARY

273 Healthcare Reform After SCOTUS: Hard Decisions Needed to Avoid Health Sector Meltdown Joseph R. Antos, PhD BUSINESS

280 Curbing the Costly Trend: Exploring the Need for a Progressive Approach to the Management of Specialty Pharmaceuticals Under the Medical Benefit Michael S. Jacobs, RPh; Kjel A. Johnson, PharmD, BCPS, FCCP, FAMCP 289 Stakeholder Perspective by James T. Kenney, Jr, RPh, MBA Continued on page 266

Publisher Nicholas Englezos nick@engagehc.com 732-992-1884 Editorial Director Dalia Buffery dalia@engagehc.com 732-992-1889 Associate Publisher Maurice Nogueira maurice@engagehc.com 732-992-1895 Associate Editor Lara J. Lorton lara@engagehc.com 732-992-1892 Executive Vice President Engage Managed Markets Chuck Collins ccollins@engagehc.com 732-992-1894 Editorial Assistant Jennifer Brandt jbrandt@the-lynx-group.com 732-992-1536 National Accounts Manager Zach Ceretelle zach@engagehc.com 732-992-1898 Senior Production Manager Lynn Hamilton Quality Control Director Barbara Marino Business Manager Blanche Marchitto Founding Editor-in-Chief Robert E. Henry

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American Health & Drug Benefits is founded on the concept that health and drug benefits have undergone a transformation: the econometric value of a drug is of equal importance to clinical outcomes as it is to serving as the basis for securing coverage in formularies and benefit designs. Because benefit designs are greatly affected by clinical, business, and policy conditions, this journal offers a forum for stakeholder integration and collaboration toward the improvement of healthcare. This publication further provides benefit design decision makers the integrated industry information they require to devise formularies and benefit designs that stand up to today’s special healthcare delivery and business needs.

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VOLUME 5, NUMBER 5

THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

TABLE OF CONTENTS

(Continued)

CLINICAL

291 Anticoagulant Use for Prevention of Stroke in a Commercial Population with Atrial Fibrillation Aarti A. Patel, PharmD, MBA; Barb Lennert, RN, BSN, MAOM; Brian Macomson, PharmD; Winnie W. Nelson, PharmD; Gary M. Owens, MD; Samir H. Mody, PharmD, MBA; Jeff Schein, DrPH, MPH 297 Stakeholder Perspective by Jack E. Fincham, PhD, RPh 310 Conceptual and Analytical Considerations toward the Use of Patient-Reported Outcomes in Personalized Medicine Demissie Alemayehu, PhD; Joseph C. Cappelleri, PhD, MPH 316 Stakeholder Perspective by Michael F. Murphy, MD, PhD DEPARTMENT

INDUSTRY TRENDS 301 Cost Management through Care Management: A Perspective on Choosing the Right Specialty Pharmacy Partner, PART 1 Michael Einodshofer, RPh, MBA; Stephen Kansler

American Health & Drug Benefits, ISSN 1942-2962 (print); ISSN 1942-2970 (online), is published 8 times a year by Engage Healthcare Communications, LLC, 1249 South River Rd, Suite 202A, Cranbury, NJ 08512. Copyright © 2012 by Engage Healthcare Communications, LLC. All rights reserved. American Health & Drug Benefits and The Peer-Reviewed Forum for Evidence in Benefit Design are trademarks of Engage Healthcare Communications, LLC. No part of this publication may be reproduced or transmitted in any form or by any means now or hereafter known, electronic or mechanical, including photocopy, recording, or any informational storage and retrieval system, without written permission from the Publisher. Printed in the United States of America. Address all editorial correspondence to: editorial@engagehc.com Telephone: 732-992-1892 Fax: 732-992-1881 American Health & Drug Benefits 1249 South River Rd, Suite 202A, Cranbury, NJ 08512 The ideas and opinions expressed in American Health & Drug Benefits do not necessarily reflect those of the Editorial Board, the Editors, or the Publisher. Publication of an advertisement or other product mentioned in American Health & Drug Benefits should not be construed as an endorsement of the product or the manufacturer’s claims. Readers are encouraged to contact the manufacturers about any features or limitations of products mentioned. Neither the Editors nor the Publisher assume any responsibility for any injury and/or damage to persons or property arising out of or related to any use of the material mentioned in this publication. For permission to reuse material from American Health & Drug Benefits (ISSN 1942-2962), please access www. copyright.com <http://www.copyright. com/> or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400.

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EDITORIAL

“SCOTUS Redux” David B. Nash, MD, MBA Editor-in-Chief, American Health & Drug Benefits; Jefferson School of Population Health, Philadelphia, PA

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ell, they certainly surprised me. On June 28, 2012, the Supreme Court Justices caught the entire policy community by surprise with their 5 to 4 decision to uphold the constitutionality of the Affordable Care Act (ACA). I would like to revisit some of the take-home messages from my May/June editorial1 in light of the Supreme Court decision, from the perspective of my service on 3 boards—the Board of Trustees for the Main Line Health System (MLHS), a very successful, high-quality, 4-hospital community-based system in suburban Philadelphia, PA; Humana Corporation, a major health insurance plan headquartered in Louisville, KY; and Endo Health Solutions, a publicly held company headquartered in Chadds Ford, PA. My board service provides me with a unique opportunity to evaluate the Supreme Court decision from different perspectives. In my previous editorial, I likened the ACA to 2 laws in 1: one aspect deals with insurance reform, and the other deals with delivery reform. The Court upheld the insurance reform component of the law and, in so doing, sent a clear signal to the healthcare industry to move forward with the delivery system reforms that have been under way for the past 2 years. By confirming the constitutionality of the individual mandate, our industry can now breathe a collective sigh of relief. We can see the “handwriting on the wall.” My position remains unchanged: We must improve the health of the population, enhance the experience of care, and decrease costs by reducing waste. We must embrace the triple aim of care, health, and cost, as articulated by Donald M. Berwick and colleagues several years ago.2 We must find a way to move from a volumebased financial model to one that compensates providers based on the value derived from the services we provide. As the Chair of the Board’s Quality and Safety Committee for MLHS and a member of the Executive Committee, I am very pleased with the Supreme Court decision. It means that we can continue with the important work of measuring and improving the quality and safety of care delivered by all of the hardworking physicians, nurses, pharmacists, and other participants in our system. In an e-mail sent to all MLHS employees on June 29, 2012, President and Chief Executive Officer (CEO) John J. (Jack) Lynch, III, wrote, “To survive in

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this new era of healthcare, physicians, hospitals, and health systems will be held to the highest standards in delivering clinical excellence and a superior patient experience. For many years, we have worked together diligently to ensure we are providing the highest quality care to every patient who comes through our doors. Our efforts to create a culture of safety have garnered repeated recognition from independent organizations and our focus on creating efficiencies and reducing costs across the system is bearing fruit.”3 All I can add to Mr Lynch’s admonition is, “Amen.” The work of the Quality and Safety Committee will continue with a new sense of purpose and urgency. Humana is a very different organization from MLHS. Humana is a Fortune 100 company with a long tradition of innovation in healthcare, and I am the only physician on the board. From my vantage point, I would view the confirmation of the ACA as a very positive development. It means that Humana can continue its strategy toward excellence in wellness and prevention. This strategy is aimed at expanding the company’s ability to provide comprehensive and integrated services across the healthcare spectrum. For example, Humana purchased Concentra, Inc, which is based in Addison, TX. Concentra provides drug screening and care for workplace injuries, and it brought with it hundreds of physicians in markets where Humana is already active. In addition to Concentra, Humana purchased Senior Bridge, a New York–based chronic care provider, and Anvita, a San Diego–based healthcare data analytics company. Concentra, Senior Bridge, and Anvita will equip Humana with the resources it needs to better integrate all aspects of care. I would argue that only the managed care industry has the economic incentives to promote prevention and wellness, a strategy clearly aligned with population health. In fact, USA Today prominently featured a frontpage interview with Michael McCallister, the CEO of Humana, the day after the historic Supreme Court decision.4 Mr McCallister noted, “The good news is that more people will be covered. Affordability is a complicated question that we’ll have to work our way through.”4 As an Endo Health Solutions board member, I believe that the constitutionality issue will be important for

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Endo’s continued growth and development. Endo Health Solutions is composed of 4 principal segments: Endo Pharmaceuticals, the branded pharmaceutical segment of the enterprise; QualiTest, the generic pharmaceutical segment; AMS, the device segment; and HealthTronics, a leading provider of integrated urologic products, services, and solutions for urologists. David P. Holveck, the CEO of Endo, was not interviewed by the press specifically regarding the passage of the ACA, but he is an authoritative figure in the biotechnology and life sciences industry. In the most recent Endo annual report, Mr Holveck noted that, “During the past 4 years we have diversified Endo Pharmaceutical Holdings, Inc. through a series of strategic acquisitions in order to broaden our therapeutic focus, increase revenues and earnings, and transform how we create and deliver value. This approach to generating sustainable, long-term growth is based upon our belief that the changes taking place in healthcare today require a newer understanding of our customers and an updated model for how we operate as a company. Our diversification into 4 business segments—branded pharmaceuticals, generics, devices, and services—reflects this philosophy.”5 Simply put, Endo has been preparing for healthcare reform for 4 years, and it recognizes that we must move to a world focused on value for the healthcare dollars spent. I am very proud of my service on these boards. These leading organizations serve as a microcosm of where I believe our entire industry is headed. The passage and reconfirmation of the ACA are very positive developments for our country as well as for these 3 organizations.

Challenges remain, however, and of course the “elephant in the room” moving forward is indeed affordability. States will be struggling with other aspects of the ACA, including the expansion of Medicaid and its related activities. Although I certainly applaud the creation of multiple demonstration projects focused on new reimbursement paradigms to pay hospitals and physicians, it remains clear that without dramatic delivery system reform, we will continue to suffer inexorable cost increases. Where do we go from here? Speaking as the editor-inchief, American Health & Drug Benefits will continue to constructively debate the question of how to achieve value for the money spent. I am confident that as we publish new research articles and commentaries and participate in the process, this journal will help to elucidate the road going forward. I hope you will join us in this critically important journey. We look forward to your direct participation. As always, you can reach me at david.nash@jeffer son.edu, or via my blog at http://nashhealthpolicy.blog spot.com. ■ References 1. Nash DB. “SCOTUS”: Will they or won’t they? Am Health Drug Benefits. 2012;5: 141-142. 2. Berwick DM, Nolan TW, Whittington J. The triple aim: care, health and cost. Health Aff (Millwood). 2008;27:759-769. 3. Lynch J. “What the supreme court decision means for MLH.” E-mail communication, June 29, 2012. 4. Mullaney T. Insurers like that health law ruling sets their path. USA Today. June 29, 2012. www.usatoday.com/news/washington/story/2012-06-28/health-care-insurers/ 55902744/1?loc=interstitialskip. Accessed July 10, 2012. 5. Endo. Exploring new pathways, forging better healthcare: Endo 2011 annual report. 2012. www.endo.com/investors/financial-reports. Accessed July 10, 2012.

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Healthcare Reform After SCOTUS: Hard Decisions Needed to Avoid Health Sector Meltdown Joseph R. Antos, PhD

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he Supreme Court upheld most of the Affordable Care Act (ACA), giving the White House cause to breathe a sigh of relief. The Court ruled the individual mandate to buy insurance constitutional, requiring only that we call the penalty for noncompliance a tax. The only real setback was in Medicaid. The federal government’s threat to take away all Medicaid funding from a state that did not expand eligibility to everyone with incomes below 133% of the poverty level was declared coercive and unconstitutional. With that caveat, proponents claim that the Obama healthcare reform will proceed as scheduled. Don’t bet on it. The Supreme Court may have settled some issues, but its decision opened up new areas of uncertainty. Will the renamed individual mandate penalty/tax be effective in leading both healthy and unhealthy people to buy insurance? Will states, facing serious fiscal problems, expand eligibility for Medicaid? More fundamentally, will the myriad changes called for by the ACA be implemented on time and with the impact promised by the White House? We have already seen a major component of the ACA fail because it promised more than it could deliver. The Community Living Assistance Services and Supports Act (better known as the CLASS Act) was a government long-term care insurance program that could not be made financially solvent and was eventually shelved.1,2 Other elements of the ACA are facing substantial challenges in implementation. Regardless of who is elected president in November, healthcare reform will be recast to fit political, economic, and practical realities that largely have been ignored for the past 4 years.

The Broccoli Question The individual mandate is constitutional, but the penalty is not—unless we call it a tax. That semantic issue consumed several days of political debate, but that Dr Antos is Wilson H. Taylor Scholar in Health Care and Retirement Policy, American Enterprise Institute, Washington, DC.

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merely splits hairs.3 The issue is not what you call it, but whether the mandate will be sufficient to avoid meltdown in the individual insurance market. The ACA imposes new federal regulations on health insurance, including guaranteed issue, no exclusions for preexisting conditions, and community rating. “Guaranteed issue” means that insurers cannot turn an applicant away, regardless of their state of health. The cost of treating any preexisting condition must be covered under the new rules, and insurers cannot charge higher premiums based on the applicant’s state of health. Unless some way is found to induce people to purchase health insurance while they are young and healthy, premiums will soar as the sick buy coverage and the healthy wait to buy it until they really need it. The combination of a mandate and generous subsidies in the insurance exchanges is supposed to be sufficient to avoid a collapse of the individual insurance market. But Congress defanged the mandate threat. The penalty for noncompliance is small, and the ACA limits the ability of the Internal Revenue Service (IRS) to collect the penalty. In 2014, the penalty is $95, or 1% of a person’s income. It grows to $695, or 2.5% of a person’s income, by 2016. However, premiums charged on the insurance exchanges will be higher than the penalty for most people. Those with incomes above 133% of the poverty level will be charged between 3% and 9% of their income for insurance if they are eligible for exchange subsidies. As a simple matter of arithmetic, delaying an insurance purchase is money in the bank if you do not need healthcare. A young person struggling to cover the rent and pay a student loan—in other words, the prime target of the mandate—is likely to take the risk. Not that the penalty/tax is likely to be collected. Under the ACA, the IRS can hold back an amount from income tax refunds owed to someone who owes the mandate tax. Scofflaws will be asked to turn themselves in by checking a box on their tax form admitting to not buying insurance. If they overwithheld, and if the IRS can verify that they were, in fact, liable, then the gov-

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ernment gets its money. The threat of prosecution or other aggressive actions to enforce the mandate are simply not allowed, because Congress had no desire to anger their constituents in this matter. This leaves open the fate of the individual insurance market. States that adopted guaranteed issue regulations in the 1990s to increase insurance coverage found that coverage fell. New Jersey’s experience was typical, with an approximate 65% decline in individual market enrollment between 1995 and 2005, while premiums increased by 50% or more annually.4,5 The Congressional Budget Office assumed that most uninsured people would want to obey the law. If this “behavioral economics” theory is correct, a broad mix of people will buy insurance, and healthy people will not drop out despite the cost they would pay. If enough people do the math and their personal circumstances cause them to take the risk—which could be minimal if the exchanges allow people to enroll at any time—then premiums will increase and healthier people will be driven from the market.

The Exchanges The ACA directs states to establish health insurance exchanges where individuals can purchase coverage. Most states have no experience operating health insurance exchanges, and even Massachusetts will find that the federal requirements differ from the rules adopted in its 2006 reform.6 Although 49 of the 50 states have received federal grants to develop their exchanges, there is a decided lack of enthusiasm in many states to take on this task.7

Creating an exchange involves extremely complex tasks, requiring careful deliberation and consultation with insurers and others to ensure that actions taken do not have unforeseen adverse consequences. As of mid-July, only 16 states have taken formal action (either through state legislation or an executive order) to establish an exchange, and 1 state will partner with the US Department of Health and Human Services (HHS) in creating an exchange.8 Seven states—Alaska, Florida, Louisiana, Maine, New Hampshire, South Carolina, and Texas—have decided not to establish an exchange, and another 10 states have taken no action over the past 2 years. The remaining states are studying the matter. It is not surprising that the states have not rushed into implementing the ACA. Some governors will not move

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forward as a matter of politics. Some states are cautious, waiting for the fall election before deciding whether to commit significant resources to exchange development. But almost all states have concerns about the complex requirements and their capacity to implement, operate, and finance the health insurance exchange over the long-term. New processes and standards must be established for functions that have never been needed before.9 Exchanges must certify qualifying health plans, which have to satisfy requirements for adequate provider networks, access to essential community providers, essential benefits, actuarial value standards, marketing, and other performance standards. Exchanges must also facilitate enrollment in health plans, which requires creating “navigators” to provide consumer education, determining whether individuals are eligible for Medicaid or for exchange subsidies, and determining whether individuals are exempt from the health insurance mandate, among other duties. To do this, states must interpret thousands of pages of federal regulations, create their own implementing regulations (which may require enactment of new state laws), and translate all of that into concrete actions. Information on income, citizenship, and other personal data must be obtained from federal agencies before subsidies can be paid. In some critical areas, the federal government has avoided the formal regulatory process, opting to issue “guidance” that does not have the full force of law. This throws particularly sensitive issues, such as the definition of essential benefits, into the laps of the states.10 There is a current tempest over whether the federal exchange can fill in for states that do not create their own entity. Some argue that states should leave it to the federal exchange, both as a political matter and because they believe that this would protect employers in those states from fines if their health plans do not satisfy federal requirements.11,12 The argument is that federal exchanges lack the authority to provide subsidies, which negates other provisions of the ACA. Others assert that a drafting error, not congressional intent, caused this result.13 Although the courts are likely to side with the White House on this issue, it remains a concern at least in the red states. Creating an exchange involves extremely complex tasks, requiring careful deliberation and consultation with insurers and others to ensure that actions taken do not have unforeseen adverse consequences. It is clear that many states will not have their insurance exchanges operating in time to enroll their citizens in exchange plans before they become liable for the mandate/tax in January 2014. States have only until November 16 to

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tell HHS whether they will implement an exchange.14,15 HHS must approve those state plans by January 1, 2014, and certify that the exchanges meet federal standards by June 2014. That schedule allows little time for insurers to develop business plans and get them approved in time to be available to consumers a little more than a year from now. Despite vague claims to the contrary, it is doubtful that the federal government—which carefully describes its role as facilitating the state’s exchange rather than running a federal exchange—will be capable of stepping in.16 The task is too large, and the time is too short.

The Medicaid Expansion The Supreme Court has given the states another difficult decision to make. They now can decide for themselves whether to expand their Medicaid programs without the potential loss of billions of dollars in federal support. Although the lure of full funding for newly eligible enrollees remains for the first 3 years, eventually states would be responsible for 10% of the cost of services, and they also would have to cover 50% of all additional administrative costs. For states facing serious financial difficulties, that does not look like free money. Most state budgets are in crisis, in large part because of underfunded public employee pensions.17 Governor Mitch Daniels pointed out that the full Medicaid expansion would cost Indiana $2 billion over 10 years, and other governors have expressed similar concerns.18 With the Court’s decision, there are new options. Even states that favor expanding Medicaid are likely to think twice before proceeding. If states expand Medicaid eligibility to include everyone with incomes below 133% of the poverty level, state funds will begin to cover an increasing share of the cost beginning in 2018. If states expand Medicaid eligibility to those at or below the poverty line, those between 100% and 133% of the poverty level could receive subsidized coverage through the exchanges. Instead of using state funds for that coverage, the cost would shift completely to the federal budget. Coverage in the exchanges will be more expensive than Medicaid because private insurers pay providers more for their services, which provides better access and potentially higher quality care. The additional federal cost is likely to run between $50 billion and $90 billion over 10 years.19 States would incur no cost for health services, would save on their administrative costs, and would gain political points for providing a better healthcare alternative to many of their low-income residents. It is too early to tell whether states will expand Medicaid coverage, and if so, to what extent. Higherincome states already have more lenient enrollment

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requirements, but low-income states are likely to be hard-pressed to expand Medicaid significantly, even on the generous terms offered by the ACA. One thing will not change, however. Medicaid will remain the insurer of last resort for patients and providers because of low payment rates and limited access to services.

Wait Until Next Year Despite enthusiastic claims that the Supreme Court resolved the uncertainty surrounding the ACA, much uncertainty remains. As discussed above, there are many uncertainties about how specific provisions will be implemented. But the biggest unknown is the most basic. Will the ACA be implemented at all?

Despite enthusiastic claims that the Supreme Court resolved the uncertainty surrounding the ACA, much uncertainty remains. If Mitt Romney is elected president, he has promised to repeal the ACA. Like all campaign promises, that is not exactly true. Mr Romney could repeal the spending and revenue provisions through the reconciliation process if Republicans hold the House and gain 50 votes in the Senate. Other provisions, including the insurance regulations, would remain, but would likely be modified in subsequent legislation. Some health sector changes that were triggered by passage of the ACA will continue regardless of any government action, and other provisions of the law will be kept in some form under a Republican health reform. Insurers announced that they will continue to allow children up to the age of 26 years to remain on their parents’ policy, even without the ACA requirement.20 Accountable care organizations are here to stay, although not necessarily the way the Medicare program wants them. The ACA has accelerated the trend toward greater provider consolidation, with hospitals buying up physician practices and other business arrangements that will increase their market power and drive up prices to private payers. Employers, who have been cutting back their employee health benefits, redoubled their efforts to keep benefit costs down to avoid incurring the “Cadillac” tax on high-cost coverage. These and other trends will continue regardless of who is in office. Whoever is president next year will face stubbornly high unemployment rates, slow economic growth, and the possibility of a double-dip recession. The federal government will once again be in a debt crisis, reaching the $16.4-trillion debt limit in early 2014. Unlike last year’s

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deal, which failed to alter government policy and defaulted to a sequester that no one likes, the debt limit negotiations will include substantive changes in programs—including health programs.21 If President Barack Obama serves a second term, fiscal pressure and the real possibility that his signature domestic policy achievement could break down under the weight of an overly ambitious implementation schedule may force him to a compromise that is more in line with Republican views. That could mean delaying and downsizing, with the states allowed to proceed at their own pace.

The confluence of a debt crisis, an economic crisis, and a healthcare sector crisis is our best chance yet for policymakers to take those problems seriously and to not simply kick them down the road. Substantial spending reductions would be necessary as part of a debt ceiling increase, and that is likely to mean sharp reductions in exchange subsidies and Medicaid matching rates for the newly eligible population. New reductions in Medicare payments to providers are virtually certain, but they could be accompanied by restructuring that would begin to look like the premium support model that Mr Romney supports. The options are limited and politically difficult, but necessary. Healthcare spending at all levels—federal, state, local, and individual—is growing faster than we are willing and able to accommodate over the long-term. The confluence of a debt crisis, an economic crisis, and a healthcare sector crisis is our best chance yet for policymakers to take those problems seriously and to not simply kick them down the road. ■ Author Disclosure Statement Dr Antos reported no conflicts of interest.

References 1. Montgomery L. Proposed long-term insurance program raises questions. Washington Post. October 27, 2009. www.washingtonpost.com/wp-dyn/content/article/

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2009/10/27/AR2009102701417.html. Accessed July 24, 2012. 2. Greenlee K. Memorandum to HHS Secretary Kathleen Sebelius on the CLASS Program. October 14, 2011. http://aspe.hhs.gov/daltcp/Reports/2011/class/CLASS memo.shtml. Accessed July 24, 2012. 3. Peters JW. Romney now says health mandate by Obama is a tax. New York Times. July 4, 2012:A1. www.nytimes.com/2012/07/05/us/politics/romney-says-health-caremandate-is-a-tax.html. Accessed July 24, 2012. 4. NJ Division of Insurance, Historical Comparison of Enrollment, February 21, 2012. www.state.nj.us/dobi/division_insurance/ihcseh/enroll/4q11historical.pdf. Accessed July 24, 2012. 5. Wachenheim L, Leida H. The impact of guaranteed issue and community rating reforms on states’ individual insurance markets. March 2012. www.ahipcoverage.com/ wp-content/uploads/2012/03/Updated-Milliman-Report.pdf. Accessed July 24, 2012. 6. Kaiser Family Foundation. Massachusetts health care reform: six years later. May 2012. www.kff.org/healthreform/upload/8311.pdf. Accessed July 24, 2012. 7. HealthCare.gov. Creating a new competitive marketplace: affordable insurance exchanges. Updated May 16, 2012. www.healthcare.gov/news/factsheets/exchanges 05232011a.html. Accessed July 24, 2012. 8. The Henry J. Kaiser Family Foundation. State action toward creating health insurance exchanges, as of July 17, 2012. www.statehealthfacts.org/comparetable.jsp? ind=962&cat=17&sub=205&yr=1&typ=5. Accessed July 24, 2012. 9. National Association of Insurance Commissioners. American Health Benefit Exchange Model Act. November 22, 2010. www.naic.org/documents/committees_b_ exchanges_adopted_health_benefit_exchanges.pdf. Accessed July 24, 2012. 10. Health policy brief: essential health benefits. Health Affairs. April 25, 2012. http://healthaffairs.org/healthpolicybriefs/brief_pdfs/healthpolicybrief_68.pdf. Accessed July 24, 2012. 11. Feder JL, Millman J. Exchanges hit roadblocks in red states. Politico. Updated April 30, 2012. www.politico.com/news/stories/0412/75331.html. Accessed July 24, 2012. 12. Adler JH, Cannon MF. Taxation without representation: the illegal IRS rule to expand tax credits under the PPACA. July 16, 2012. http://papers.ssrn.com/sol3/ papers.cfm?abstract_id=2106789##. Accessed July 24, 2012. 13. Pear R. Brawling over health care moves to rules on exchanges. New York Times. July 7, 2012. www.nytimes.com/2012/07/08/us/critics-of-health-care-law-prepare-tobattle-over-insurance-exchange-subsidies.html. Accessed July 24, 2012. 14. Centers for Medicare & Medicaid Services, Center for Consumer Information and Insurance Oversight. General guidance on federally-facilitated exchanges. May 16, 2012. http://cciio.cms.gov/resources/files/FFE_Guidance_FINAL_VERSION_ 051612.pdf. Accessed July 24, 2012. 15. Centers for Medicare & Medicaid Services, Center for Consumer Information and Insurance Oversight. Draft blueprint for approval of affordable state-based and state partnership insurance exchanges. http://cciio.cms.gov/resources/files/Exchange blueprint05162012.pdf. Accessed July 24, 2012. 16. Sack K, Abelson R. States face a challenge to meet health law’s deadline. New York Times. June 28, 2012. www.nytimes.com/2012/06/29/us/states-face-a-challengeto-hit-laws-deadlines.htm. Accessed July 24, 2012. 17. Ross AC. Underfunded state pension plans create credit risk. The Fiscal Times. April 1, 2011. www.thefiscaltimes.com/Articles/2011/04/01/Underfunded-State-PensionPlans-Create-Credit-Risk.aspx. Accessed July 24, 2012. 18. Pear R. Uncertainty over states and Medicaid expansion. New York Times. June 28, 2012. www.nytimes.com/2012/06/29/us/uncertainty-over-whether-states-will-chooseto-expand-medicaid.html. Accessed July 24, 2012. 19. Antos J. After the Supreme Court, higher cost and unrealistic timeline will force major changes. Health Affairs Blog. July 2, 2012. http://healthaffairs.org/blog/2012/ 07/02/after-the-supreme-court-higher-cost-and-unrealistic-timeline-will-forcemajor-changes/. Accessed July 24, 2012. 20. Appleby J. 3 large insurers promise to keep many popular features of health law if high court strikes it down. Kaiser Health News. June 11, 2012. www.kaiserhealth news.org/Stories/2012/June/11/UnitedHealthcare-insurance-supreme-court.aspx. Accessed July 24, 2012. 21. Prial D. ‘No’ to compromise means ‘Yes’ to sequestration. Fox Business. May 11, 2012. www.foxbusiness.com/government/2012/05/10/no-to-compromise-means-yesto-sequestration/. Accessed July 24, 2012.

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IMPORTANT SAFETY AND ELIGIBILITY INFORMATION FluMist Quadrivalent is a vaccine indicated for active immunization of persons 2-49 years of age for the prevention of influenza disease caused by influenza A subtype viruses and type B viruses contained in the vaccine. FluMist Quadrivalent is for intranasal administration only. FluMist Quadrivalent is contraindicated in persons who have had a severe allergic reaction to any vaccine component including egg protein, gentamicin, gelatin and arginine or after a previous dose of any influenza vaccine, and in children and adolescents receiving concomitant aspirin or aspirin-containing therapy. In clinical trials, the risks of hospitalization and wheezing were increased in children <24 months of age who received FluMist® (trivalent Influenza Vaccine Live, Intranasal). Children <5 years of age with recurrent wheezing and persons of any age with asthma may be at increased risk of wheezing following FluMist Quadrivalent administration. FluMist Quadrivalent has not been studied in persons with severe asthma or active wheezing. If Guillain-Barré syndrome has occurred within 6 weeks of any prior influenza vaccination, the decision to give FluMist Quadrivalent should be based on careful consideration of the potential benefits and risks. FluMist Quadrivalent has not been studied in immunocompromised persons. The safety of FluMist Quadrivalent in individuals with underlying medical conditions predisposing them to wild-type influenza infection complications has not been established. FluMist Quadrivalent may not protect all individuals receiving the vaccine. The most common solicited adverse reactions (occurring >10% in vaccine recipients and at least 5% greater than in placebo) reported after FluMist were runny nose or nasal congestion in all persons 2-49 years, fever >100ºF in children 2-6 years, and sore throat in adults 18-49 years. Among children 2-17 years who received FluMist Quadrivalent, 32% reported runny nose or nasal congestion and 7% reported fever >100ºF. Among adults 18-49 years who received FluMist Quadrivalent, 44% reported runny nose or nasal congestion and 19% reported sore throat. Please see accompanying brief summary on the following pages. Reference: 1. FluMist Quadrivalent [package insert]. Gaithersburg, MD: MedImmune, LLC.

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Brief Summary of Prescribing Information FluMist® Quadrivalent Influenza Vaccine Live, Intranasal Intranasal Spray 20XX-20XX Formula INDICATIONS AND USAGE FluMist® Quadrivalent is a vaccine indicated for active immunization for the prevention of influenza disease caused by influenza A subtype viruses and type B viruses contained in the vaccine. FluMist Quadrivalent is approved for use in persons 2 through 49 years of age. DOSAGE AND ADMINISTRATION FOR INTRANASAL ADMINISTRATION BY A HEALTHCARE PROVIDER. Dosing Information Administer FluMist Quadrivalent according to the following schedule: Vaccination Status Age Group Not previously Children age 2 years vaccinated with through 8 years influenza vaccine Previously vaccinated Children age 2 years through 8 years with influenza vaccine Children, adolescents, and adults age 9 Not applicable through 49 years

Dosage Schedule 2 doses (0.2 mL* each, at least 1 month apart) 1 dose (0.2 mL*) 1 dose (0.2 mL*)

*Administer as 0.1 mL per nostril. CONTRAINDICATIONS Severe Allergic Reactions Do not administer FluMist Quadrivalent to persons who have had a severe allergic reaction (e.g., anaphylaxis) to any component of the vaccine including egg protein, gentamicin, gelatin, and arginine, or after a previous dose of any influenza vaccine. Concomitant Aspirin Therapy and Reye’s Syndrome in Children and Adolescents Do not administer FluMist Quadrivalent to children and adolescents through 17 years of age who are receiving aspirin therapy or aspirin-containing therapy because of the association of Reye’s syndrome with aspirin and wild-type influenza infection. WARNINGS AND PRECAUTIONS Risks of Hospitalization and Wheezing in Children Younger than 24 Months of Age In clinical trials, risks of hospitalization and wheezing were increased in children younger than 2 years of age who received FluMist (trivalent Influenza Vaccine Live, Intranasal). This observation with FluMist is relevant to FluMist Quadrivalent because both vaccines are manufactured using the same process and have overlapping compositions. Asthma, Recurrent Wheezing, and Active Wheezing Children younger than 5 years of age with recurrent wheezing and persons of any age with asthma may be at increased risk of wheezing following administration of FluMist Quadrivalent. FluMist Quadrivalent has not been studied in persons with severe asthma or active wheezing. Guillain-Barré Syndrome The 1976 swine influenza vaccine (inactivated) was associated with an elevated risk of GuillainBarré syndrome (GBS). Evidence for causal relation of GBS with other influenza vaccines is inconclusive; if an excess risk exists, based on data for inactivated influenza vaccines, it is probably slightly more than 1 additional case per 1 million persons vaccinated. If GBS has occurred within 6 weeks of any prior influenza vaccination, the decision to give FluMist Quadrivalent should be based on careful consideration of the potential benefits and potential risks. Altered Immunocompetence FluMist Quadrivalent has not been studied in immunocompromised persons. The effectiveness of FluMist has not been studied in immunocompromised persons. Data on safety and shedding of vaccine virus after administration of FluMist in immunocompromised persons are limited to 174 persons with HIV infection and 10 mild to moderately immunocompromised children and adolescents with cancer. Medical Conditions Predisposing to Influenza Complications The safety of FluMist Quadrivalent in individuals with underlying medical conditions that may predispose them to complications following wild-type influenza infection has not been established. Management of Acute Allergic Reactions Appropriate medical treatment and supervision must be available to manage possible anaphylactic reactions following administration of the vaccine. Limitations of Vaccine Effectiveness FluMist Quadrivalent may not protect all individuals receiving the vaccine. ADVERSE REACTIONS Clinical Trials Experience Because clinical trials are conducted under widely varying conditions, adverse reaction rates observed in the clinical trials of a vaccine cannot be directly compared to rates in the clinical trials of another vaccine and may not reflect the rates observed in practice. This safety experience with FluMist is relevant to FluMist Quadrivalent because both vaccines are manufactured using the same process and have overlapping compositions. A total of 9537 children and adolescents 1 through 17 years of age and 3041 adults 18 through 64 years of age received FluMist in randomized, placebo-controlled Studies D153-P501, AV006, D153-P526, AV019, and AV009 [3 used Allantoic Fluid containing Sucrose-Phosphate-Glutamate (AF-SPG) placebo, and 2 used saline placebo] described below. In addition, 4179 children 6 through 59 months of age received FluMist in Study MI-CP111, a randomized, active-controlled trial. Among pediatric FluMist recipients 6 months through 17 years of age, 50% were female; in the study of adults, 55% were female. In MI-CP111, AV006, D153-P526, AV019, and AV009, subjects were White (71%), Hispanic (11%), Asian (7%), Black (6%), and Other (5%), while in D153-P501, 99% of subjects were Asian. A total of 1382 children and adolescents 2 through 17 years of age and 1198 adults 18 through 49 years of age received FluMist Quadrivalent in randomized, active-controlled Studies MI-CP208 and MI-CP185. Among pediatric FluMist Quadrivalent recipients 2 through 17 years of age, 51% were female; in the study of adults, 55% were female. In Studies MI-CP208 and MI-CP185, subjects were White (73%), Asian (1%), Black or African-American (19%), and Other (7%); overall, 22% were Hispanic or Latino.

FluMist in Children and Adolescents The safety of FluMist was evaluated in an AF-SPG placebo-controlled study (AV019) conducted in a Health Maintenance Organization (HMO) in children 1 through 17 years of age (FluMist = 6473, placebo = 3216). An increase in asthma events, captured by review of diagnostic codes, was observed in children younger than 5 years of age who received FluMist compared to those who received placebo (Relative Risk 3.53, 90% CI: 1.1, 15.7). In Study MI-CP111, children 6 through 59 months of age were randomized to receive FluMist or inactivated Influenza Virus Vaccine manufactured by Sanofi Pasteur Inc. Wheezing requiring bronchodilator therapy or accompanied by respiratory distress or hypoxia was prospectively monitored from randomization through 42 days post last vaccination. Hospitalization due to all causes was prospectively monitored from randomization through 180 days post last vaccination. Increases in wheezing and hospitalization (for any cause) were observed in children 6 months through 23 months of age who received FluMist compared to those who received inactivated Influenza Virus Vaccine, as shown in Table 1. Table 1: Percentages of Children with Hospitalizations and Wheezing from Study MI-CP111a Adverse Reaction Age Group FluMist Active Controlb (n/N) (n/N) 6-23 months 4.2 % 3.2 % Hospitalizationsc (63/1975) (84/1992) 24-59 months 2.1 % 2.5 % (56/2198) (46/2187) d 5.9 % 3.8 % Wheezing 6-23 months (117/1992) (75/1975) 2.1 % 2.5 % 24-59 months (47/2187) (56/2198) a

NCT00128167; see www.clinicaltrials.gov Inactivated Influenza Virus Vaccine manufactured by Sanofi Pasteur Inc., administered intramuscularly. c Hospitalization due to any cause from randomization through 180 days post last vaccination. d Wheezing requiring bronchodilator therapy or accompanied by respiratory distress or hypoxia evaluated from randomization through 42 days post last vaccination. Most hospitalizations observed were due to gastrointestinal and respiratory tract infections and occurred more than 6 weeks post vaccination. In post-hoc analysis, rates of hospitalization in children 6 through 11 months of age were 6.1% (42/684) in FluMist recipients and 2.6% (18/683) in inactivated Influenza Virus Vaccine recipients. Table 2 shows pooled solicited adverse reactions occurring in at least 1% of FluMist recipients and at a higher rate (≥ 1% rate difference after rounding) compared to placebo post Dose 1 for Studies D153-P501 and AV006, and solicited adverse reactions post Dose 1 for Study MI-CP111. Solicited adverse reactions were those about which parents/guardians were specifically queried after receipt of FluMist, placebo, or control vaccine. In these studies, solicited reactions were documented for 10 days post vaccination. Solicited reactions following the second dose of FluMist were similar to those following the first dose and were generally observed at a lower frequency. Table 2: Summary of Solicited Adverse Reactions Observed Within 10 Days after Dose 1 for FluMist and Either Placebo or Active Control Recipients in Children 2 through 6 Years of Age a b Study MI-CP111 Studies D153-P501 & AV006 c FluMist Placebo FluMist Active Controld e e e e N=876-1759 N=424-1034 N=2170 N=2165 Event % % % % Runny Nose/ 58 50 51 42 Nasal Congestion Decreased Appetite 21 17 13 12 Irritability 21 19 12 11 Decreased Activity 14 11 7 6 (Lethargy) Sore Throat 11 9 5 6 Headache 9 7 3 3 Muscle Aches 6 3 2 2 Chills 4 3 2 2 Fever > 100°F Oral 16 11 13 11 > 100- ≤101°F Oral 9 6 6 4 > 101- ≤102°F Oral 4 3 4 3 a NCT00192244; see www.clinicaltrials.gov b NCT00128167; see www.clinicaltrials.gov c Study D153-P501 used saline placebo; Study AV006 used AF-SPG placebo. d Inactivated Influenza Virus Vaccine manufactured by Sanofi Pasteur Inc., administered intramuscularly. e Number of evaluable subjects (those who returned diary cards) for each reaction. Range reflects differences in data collection between the 2 pooled studies. In clinical studies D153-P501 and AV006, unsolicited adverse reactions in children occurring in at least 1% of FluMist recipients and at a higher rate (≥ 1% rate difference after rounding) compared to placebo were abdominal pain (2% FluMist vs. 0% placebo) and otitis media (3% FluMist vs. 1% placebo). An additional adverse reaction identified in the active-controlled trial MI-CP111 occurring in at least 1% of FluMist recipients and at a higher rate (≥ 1% rate difference after rounding) compared to active control was sneezing (2% FluMist vs. 1% active control). In a separate saline placebo-controlled trial (D153-P526) in a subset of older children and adolescents 9 through 17 years of age who received one dose of FluMist, the solicited adverse reactions as well as unsolicited adverse reactions reported were generally consistent with observations from the trials in Table 2. Abdominal pain was reported in 12% of FluMist recipients compared to 4% of placebo recipients and decreased activity was reported in 6% of FluMist recipients compared to 0% of placebo recipients. In Study AV018, in which FluMist was concomitantly administered with Measles, Mumps, and Rubella Virus Vaccine Live (MMR, manufactured by Merck & Co., Inc.) and Varicella Virus Vaccine Live (manufactured by Merck & Co., Inc.) to children 12 through 15 months of age, adverse reactions were similar to those seen in other clinical trials of FluMist. FluMist Quadrivalent in Children and Adolescents In the randomized, active-controlled Study MI-CP208 that compared FluMist Quadrivalent and FluMist in children and adolescents 2 through 17 years of age, the rates of solicited adverse reactions reported were similar between subjects who received FluMist Quadrivalent and FluMist. Table 3 includes solicited adverse reactions post Dose 1 from Study MI-CP208 that either occurred at a higher rate (≥ 1% rate difference after rounding) in FluMist Quadrivalent recipients compared b


to FluMist recipients or were identified in previous FluMist clinical studies [see Table 2]. In this study, solicited adverse reactions were documented for 14 days post vaccination. Solicited adverse reactions post Dose 2 were observed at a lower frequency compared to those post Dose 1 for FluMist Quadrivalent and were similar between subjects who received FluMist Quadrivalent and FluMist. Table 3: Summary of Solicited Adverse Reactionsa Observed Within 14 Days after Dose 1 for FluMist Quadrivalent and FluMist Recipients in Study MI-CP208b in Children and Adolescents 2 through 17 Years of Age FluMist Quadrivalent N = 1341-1377d % 32 13 10 9 6 4

FluMistc N = 901-920d % 32 12 10 10 7 5

Event Runny Nose/Nasal Congestion Headache Decreased Activity (Lethargy) Sore Throat Decreased Appetite Muscle Aches Fever > 100°F by any route 7 5 > 100 - ≤ 101°F by any route 3 2 2 2 > 101 - ≤ 102°F by any route a Solicited adverse reactions that occurred at a higher rate (≥ 1% rate difference after rounding) in FluMist Quadrivalent recipients compared to FluMist recipients or were identified in previous FluMist trials [see Table 2]. b NCT01091246; see www.clinicaltrials.gov c Represents pooled data from the two FluMist study arms. d Number of evaluable subjects for each event. In Study MI-CP208, no unsolicited adverse reactions occurred at a higher rate (1% or greater) in FluMist Quadrivalent recipients compared to FluMist recipients. FluMist in Adults In adults 18 through 49 years of age in Study AV009, solicited adverse reactions occurring in at least 1% of FluMist recipients and at a higher rate (≥ 1% rate difference after rounding) compared to AF-SPG placebo include runny nose (44% FluMist vs. 27% placebo), headache (40% FluMist vs. 38% placebo), sore throat (28% FluMist vs. 17% placebo), tiredness/weakness (26% FluMist vs. 22% placebo), muscle aches (17% FluMist vs. 15% placebo), cough (14% FluMist vs. 11% placebo), and chills (9% FluMist vs. 6% placebo). In Study AV009, unsolicited adverse reactions occurring in at least 1% of FluMist recipients and at a higher rate (≥ 1% rate difference after rounding) compared to placebo were nasal congestion (9% FluMist vs. 2% placebo) and sinusitis (4% FluMist vs. 2% placebo). FluMist Quadrivalent in Adults In the randomized, active-controlled Study MI-CP185 that compared FluMist Quadrivalent and FluMist in adults 18 through 49 years of age, the rates of solicited adverse reactions reported were generally similar between subjects who received FluMist Quadrivalent and FluMist. Table 4 presents solicited adverse reactions that either occurred at a higher rate (≥ 1% rate difference after rounding) in FluMist Quadrivalent recipients compared to FluMist recipients or were identified in Study AV009. Table 4: Summary of Solicited Adverse Reactionsa Observed Within 14 Days after Dose 1 for FluMist Quadrivalent and FluMist Recipients in Study MI-CP185b in Adults 18 through 49 Years of Age FluMist Quadrivalent FluMistc N = 1197d N = 597d Event % % Runny Nose/Nasal Congestion 44 40 Headache 28 27 Sore Throat 19 20 Decreased Activity (Lethargy) 18 18 Cough 14 13 Muscle Aches 10 10 Decreased Appetite 6 5 a Solicited adverse reactions that occurred at a higher rate (≥ 1% rate difference after rounding) in FluMist Quadrivalent recipients compared to FluMist recipients or were identified in Study AV009. b NCT00860067; see www.clinicaltrials.gov c Represents pooled data from the two FluMist study arms. d Number of evaluable subjects for each event. In Study MI-CP185, no unsolicited adverse reactions occurred at a higher rate (1% or greater) in FluMist Quadrivalent recipients compared to FluMist recipients. Postmarketing Experience The following events have been spontaneously reported during post approval use of FluMist. Because these events are reported voluntarily from a population of uncertain size, it is not always possible to reliably estimate their frequency or establish a causal relationship to vaccine exposure. Cardiac disorders: Pericarditis Congenital, familial, and genetic disorders: Exacerbation of symptoms of mitochondrial encephalomyopathy (Leigh syndrome) Gastrointestinal disorders: Nausea, vomiting, diarrhea Immune system disorders: Hypersensitivity reactions (including anaphylactic reaction, facial edema, and urticaria) Nervous system disorders: Guillain-Barré syndrome, Bell’s Palsy, meningitis, eosinophilic meningitis, vaccine-associated encephalitis Respiratory, thoracic, and mediastinal disorders: Epistaxis Skin and subcutaneous tissue disorders: Rash DRUG INTERACTIONS Aspirin Therapy Do not administer FluMist Quadrivalent to children and adolescents through 17 years of age who are receiving aspirin therapy or aspirin-containing therapy because of the association of Reye’s syndrome with aspirin and wild-type influenza. Avoid aspirin-containing therapy in these age groups during the first 4 weeks after vaccination with FluMist Quadrivalent unless clearly needed.

Antiviral Agents Against Influenza A and/or B Antiviral drugs that are active against influenza A and/or B viruses may reduce the effectiveness of FluMist Quadrivalent if administered within 48 hours before, or within 2 weeks after vaccination. The concurrent use of FluMist Quadrivalent with antiviral agents that are active against influenza A and/or B viruses has not been evaluated. If antiviral agents and FluMist Quadrivalent are administered concomitantly, revaccination should be considered when appropriate. Concomitant Administration with Inactivated Vaccines The safety and immunogenicity of FluMist Quadrivalent when administered concomitantly with inactivated vaccines have not been determined. Studies of FluMist and FluMist Quadrivalent excluded subjects who received any inactivated or subunit vaccine within two weeks of enrollment. Concomitant Administration with Other Live Vaccines Concomitant administration of FluMist Quadrivalent with Measles, Mumps, and Rubella Virus Vaccine Live (MMR, manufactured by Merck & Co., Inc.) or the Varicella Virus Vaccine Live (manufactured by Merck & Co., Inc.) has not been studied. Concomitant administration of FluMist with MMR and the varicella vaccine was studied in children 12 through 15 months of age. Concomitant administration of FluMist with the MMR and the varicella vaccine in children older than 15 months of age has not been studied. Intranasal Products There are no data regarding co-administration of FluMist Quadrivalent with other intranasal preparations. USE IN SPECIFIC POPULATIONS Pregnancy Pregnancy Category B A developmental and reproductive toxicity study has been performed in female rats administered FluMist Quadrivalent either three times (during the period of organogenesis) or six times (prior to gestation and during the period of organogenesis), 200 microliter/rat/occasion (approximately 150 human dose equivalents), by intranasal instillation and has revealed no evidence of impaired fertility or harm to the fetus due to FluMist Quadrivalent. There are however, no adequate and well controlled studies in pregnant women. Because animal studies are not always predictive of human response FluMist Quadrivalent should be administered during pregnancy only if clearly needed. Nursing Mothers It is not known whether FluMist Quadrivalent is excreted in human milk. Because some viruses are excreted in human milk, caution should be exercised when FluMist Quadrivalent is administered to a nursing woman. Pediatric Use Safety and effectiveness of FluMist Quadrivalent in children 24 months of age and older is based on data from FluMist clinical studies and a comparison of post-vaccination antibody titers between persons who received FluMist Quadrivalent and those who received FluMist. FluMist Quadrivalent is not approved for use in children younger than 24 months of age because use of FluMist in children 6 through 23 months has been associated with increased risks of hospitalization and wheezing in clinical trials. Geriatric Use FluMist Quadrivalent is not approved for use in persons 65 years of age and older because in a clinical study (AV009), effectiveness of FluMist to prevent febrile illness was not demonstrated in adults 50 through 64 years of age. In this study, solicited events among individuals 50 through 64 years of age were similar in type and frequency to those reported in younger adults. In a clinical study of FluMist in persons 65 years of age and older, subjects with underlying high-risk medical conditions (N = 200) were studied for safety. Compared to controls, FluMist recipients had a higher rate of sore throat. PATIENT COUNSELING INFORMATION Vaccine recipients or their parents/guardians should be informed by the healthcare provider of the potential benefits and risks of FluMist Quadrivalent and the need for two doses at least 1 month apart in children 2 through 8 years of age who have not previously received influenza vaccine. The healthcare provider should provide the Vaccine Information Statements (VIS) which are required by the National Childhood Vaccine Injury Act of 1986 to be given with each immunization. Asthma and Recurrent Wheezing Ask the vaccinee or their parent/guardian if the vaccinee has asthma. For children younger than 5 years of age, also ask if the vaccinee has recurrent wheezing since this may be an asthma equivalent in this age group. The vaccinee or their parent/guardian should be informed that there may be an increased risk of wheezing associated with FluMist Quadrivalent in persons younger than 5 years of age with recurrent wheezing and persons of any age with asthma. Vaccination with a Live Virus Vaccine Vaccine recipients or their parents/guardians should be informed by the healthcare provider that FluMist Quadrivalent is an attenuated live virus vaccine and has the potential for transmission to immunocompromised household contacts. Adverse Event Reporting The vaccine recipient or their parent/guardian should be instructed to report adverse reactions to their healthcare provider. FluMist® is a registered trademark of MedImmune, LLC.

Manufactured by: MedImmune, LLC Gaithersburg, MD 20878 1-877-633-4411 Issue Date: February 2012 U.S. Government License No. 1799

RAL-FLUQV1 Component No.: 10951


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Review ARticle

Curbing the Costly Trend: Exploring the Need for a Progressive Approach to the Management of Specialty Pharmaceuticals Under the Medical Benefit Michael S. Jacobs, RPh; Kjel A. Johnson, PharmD, BcPS, FccP, FAMcP

Stakeholder Perspective, page 289

Am Health Drug Benefits. 2012;5(5):280-289 www.AHDBonline.com Disclosures are at end of text

Background: Specialty injectables and protein-based biologic therapies represent the fastest growing segment of the drug trend for many plan sponsors. Coupled with the decline in spending on traditional pharmaceuticals and so-called blockbuster drugs coming off patent, the upward trend of specialty drug spending continues at an unprecedented rate, precipitating a shift in the focus of payers who manage prescription drugs. Objectives: To characterize the current and future specialty drug spending and describe contemporary trends among payers for managing cost and quality in this segment, as well as to elucidate the shortcomings of the current efforts and to explore a comprehensive approach for addressing the cost and quality concerns directly associated with specialty injectables and protein-based biologics through interrelated management interventions. Discussion: Although a notable decrease in spending on traditional pharmaceuticals was realized in 2010, disproportionate increases in specialty drug utilization and cost per unit fueled the continuing growth of the injectable and biologic markets. Each course of these therapies can cost in the tens of thousands of dollars, and this upward trend of specialty spending represents an escalation of an already significant spending for payers, employers, and members. Beyond the high cost and growing utilization of specialty pharmaceuticals, current management efforts have been met with variable degrees of success and have often proved challenging and, in some cases, even counterproductive. Common interventions used by payers nationwide for addressing specialty drug spending trend include specialty drug formularies, provider reimbursement strategies, distribution channel management, benefit design modifications, utilization management, and operational and administrative improvements such as postclaim edits. Although often overlooked, appropriate implementation of these tactics, and the extent to which they are integrated with overall drug benefit management, are key to the success of the pharmaceutical management program. Conclusion: Conventional specialty pharmaceutical management initiatives offer promise in various areas, but incentives for the best protocols may be misaligned when they are applied individually. Conversely, a comprehensive approach that integrates effective components of the specialty pharmaceutical management interventions can improve the quality of care and control costs associated with these agents, with significant specialty drug management expertise and access to benchmarking data serving as the foundation for appropriate decision-making.

T

he growing impact of specialty injectables and biologic agents on the budgets of health plan sponsors is undeniable. Spending on specialty

Mr Jacobs is Vice President, National Accounts, Truveris, Inc, New York, NY, and Dr Johnson is Senior Vice President of Strategy and Business Development, Magellan Pharmacy Solutions, Orlando, FL.

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drugs has had increased influence on the â&#x20AC;&#x153;bottom lineâ&#x20AC;? of managed care over the past several years, accounting for 16.3% of plan costs and an astonishing 70.1% of the overall drug trend in 2010.1 Fueled by high costs and a drug pipeline rife with specialty and biologic medications for diseases such as cancer, rheumatoid arthritis (RA), and multiple sclerosis, it is estimated that new and existing agents of this type will continue to account for

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a majority of the drug trend by the end of 2013.1 With no end in sight, it is expected that 8 of the top 10 drugs— according to overall sales estimates—will be specialty products by 2016.1 In addition to the high price and growing popularity of biologic agents and other targeted therapies, this trend has been simultaneously amplified by the declining impact of traditional pharmaceutical therapies, largely because of the increased prevalence of generic drugs and their use. Although these traditional pharmaceutical agents contributed only 1.1% to the overall prescription drug trend in 2010, an array of so-called blockbuster drugs—collectively worth more than $50 billion in 2010 US sales—are expected to lose patent protection after 2013.1 During this same timeframe, first-time generic drugs represent a significant 20% of current plan spending on prescription drugs and 8% of total prescription claims volume, likely resulting in notable cost-savings within the nonspecialty therapeutic classes as the generic pharmacy dispensing rate dramatically increases.1 These interrelated factors have created a unique dichotomy for health plan sponsors: although the overall drug cost trend is essentially flat for nonspecialty therapeutics, specialty drug costs are escalating at an unprecedented rate.2 This dynamic within the drug cost management domain has garnered increasing attention from health plan sponsors. Because recent efforts on the part of payers have yielded only moderate success in maintaining quality of care, while controlling specialty drug spending, consideration of more comprehensive management interventions for specialty agents is warranted. Although specialty drug initiatives based on formularies, provider reimbursement, benefit design, distribution channel management, fraud and error reduction, and utilization management have been incorporated alone or in various combinations by health plans across the country, success has been variable among the various plans. This may be attributed to the availability of only few payers’ strategies that comprehensively encompass all of these components, leaving certain issues in the complex specialty drug delivery system unaddressed. With the expectation that cost pressures related to the specialty drug sector will only increase in the future, the time to explore and implement effective pharmaceutical management strategies is clearly now.

The Specialty Drug Conundrum High Cost and Growing Utilization As the fastest growing segment of drug spending, specialty pharmaceuticals represent an area of urgent concern for plan sponsors and other stakeholders.2 Although traditional drug spending decreased noticeably in 2010

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KEY POINTS ➤

Increased spending on specialty drugs—the fastest growing segment of drug spending—has had a large influence on managed care in the past several years. As the fastest growing segment of drug spending, specialty pharmaceuticals represent an area of urgent concern for plan sponsors and other stakeholders. Among the increasingly high-cost specialty medications are injectable and biologic agents, with each course of treatment ranging in the tens of thousands of dollars, resulting in significant increases in spending for payers, employers, and members. Based on a recent survey of 60 commercial health insurance plans covering 153 million lives, approximately 66% of plans have at least some established medical benefit injectable drug formulary. Key interventions by payers for addressing specialty drug spending include the use of formularies, provider reimbursement strategies, distribution channel management, benefit design modifications, utilization management, and operational and administrative improvements. A combination of these interventions can improve the quality of care and control payers’ costs. When developing a medical pharmacy management strategy, it is critical to note that the physician buyand-bill strategy continues to be the most efficient method of minimizing waste and taking advantage of the lowest acquisition costs for drugs.

(to 1.4% from 4.8% in 2009), specialty drug spending increased by 19.6% during the same period (Figure 1).2 This trend was driven by a 7.0% increase in specialty drug prevalence versus a 0.7% decrease in traditional pharmaceuticals, and by a 9.2% increase in specialty drug cost per unit compared with only a 3.5% increase in the same category for traditional pharmaceuticals.2 With courses of therapy sometimes costing tens of thousands of dollars, this increased specialty drug cost per unit represents a significant escalation in costs for payers and plan members alike. Patent expirations contributed –1.9% to the decline in traditional drug spending in 2010, and a surplus of high-volume traditional pharmacy-dispensed agents coming off patent through 2013 will undoubtedly continue this downward trend.1,2 Meanwhile, the vast majority of medications in the specialty drug segment are well within their patent lifetime, and several new agents are being added on a regular basis from a drug pipeline overflowing with experimental biologics. As of 2010, cancer has led all therapeutic areas, with 907 drugs (38% of the entire pipeline) currently in development; more of these drugs advanced to phase 2

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Figure 1 Comparative Drug Trend, 2006-2010 Traditional drug trend Overall drug trend Specialty drug trend

25%

20%

15%

10%

5%

0% 2006

2007

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Reprinted with permission from Express Scripts. 2010 Drug Trend Report. April 2011.

and 3 clinical trials in 2011 than in the previous year (Figure 2).1,3 In addition, there is yet no US Food and Drug Administration (FDA)-approved mechanism to bring a generic specialty pharmaceutical drug (ie, biosimilar) to market in the United States, thereby mitigating potential future savings in the specialty drug segment related to patent expirations. (In February 2012, the FDA issued â&#x20AC;&#x153;guidance for industryâ&#x20AC;? regarding biosimilars.4) Furthermore, although biosimilars were originally expected to generate 30% to 40% savings, recent data suggest that most payers anticipate that biosimilars will be priced at a more modest 10% to 20% less than the cost of brand-name equivalent agents, because of the complexity of bringing these drugs to market.5

Payer Interventions Beyond the high cost and growing utilization of specialty pharmaceuticals, current management efforts have been met with variable success and have often proved challenging and even counterproductive. Common interventions used by payers nationwide for addressing specialty drug spending include medical benefit drug formularies, novel provider reimbursement strategies, distribution channel management, benefit design modifications, utilization management, and operational and administrative improvements such as postclaim edits. Among the most practical and effective of these specialty management interventions, medical benefit drug formularies are widely accepted by payers and by plan members. Based on a recent survey of 60 commercial health

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insurance plans covering 153 million lives, approximately 66% of plans operate with at least some established medical benefit injectable drug formulary.3 For almost all of these plan members, formularies are available for almost all erythropoietin-stimulating agents (ESAs) and for intravenous immunoglobulin (IVIG); by contrast, approximately only 66% of biologic agents for the treatment of RA are subject to formularies.3 In addition, 57% of the members covered by the surveyed plans have access to formularies for chemotherapy agents.3 The most frequently managed chemotherapy agents included in this survey were bevacizumab (Avastin), rituximab (Rituxan), and trastuzumab (Herceptin). The benefit for health plans of using formularies in specialty drug management is 2-fold: (1) formularies allow plans to manage drug utilization in a simple, straightforward manner similar to that used under the pharmacy benefit for traditional medicines, and (2) by designating preferred agents in various drug classes, formularies can facilitate the negotiation of rebates by health plans with drug manufacturers. Plans covering 76% of the lives in the payer survey cited before reported that they receive rebates based on their implementation of a medical benefit drug formulary.3 From a plan member perspective, formulary status demonstrates a thorough clinical review, indicating that due diligence has been performed for therapies included in the formulary.3 Considered by some stakeholders to be more challenging to implement than medical benefit drug formularies, changes to provider reimbursement programs

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Figure 2 Drugs in the Pipeline in Phase 2 or 3 Clinical Trials for Key Cancer Types Phase 2 trials Phase 3 trials

Breast

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Non-Hodgkin lymphoma

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Colorectal

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Adapted from ICORE Healthcare. Medical Pharmacy & Oncology Trend Report. © 2011. Used with permission.

have, at times, yielded successful results, and at other times unfavorable results for payers and for providers alike. A deleterious outcome is often the result of reimbursement programs that produce perverse incentives. Plan stakeholders have long regarded the buy-and-bill system to be flawed, because healthcare providers prescribe therapies that allow them to generate the greatest possible income through drug margin. Today, approximately 6 of every 10 covered lives of surveyed plans reimburse providers for medical benefit injectables based on a percentage above the average sales price (ASP) methodology3 (known as “ASP plus”), which was made popular by the Medicare Modernization Act of 2005. Furthermore, based on the same payer survey, approximately only 1 in 4 covered lives are currently subject to the traditional average wholesale price provider reimbursement that once allowed administering physicians to generate significant practice revenue.3 Although switching to tighter ASP reimbursement methodology would seemingly reduce providers’ drug margins and lead to lower overall drug costs, several undesirable consequences may arise from such an approach. First, under an ASP-plus methodology, providers may be incentivized to choose higher-cost therapies to compensate for the lower reimbursement rate.3 In addition, the unfavorable reimbursement associated with ASP plus may result in fewer providers continuing to administer injectable drugs in their practices, which will

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invariably lead to increased referrals to the higher-cost hospital outpatient setting for drug administration.3 Looking at the top 10 drugs by annual spending per 1 million lives in 2010, administration in the hospital setting generally resulted in at least twice the cost of provider-administered injectables delivered in the physician’s office (Table 1).3 The high cost associated with specialty drug acquisition and/or administration via alternative means to physician buy-and-bill is likewise one reason why distribution channel management may be a challenge for payers. Some plans have taken provider reimbursement– based initiatives a step further, by removing specialty injectables from the practices’ domain or encouraging their administration in other settings. Furthermore, outside of payers’ control, the Community Oncology Alliance reported last year that more than 300 oncology practices had been purchased by hospitals in the previous 4 years.6 Although nearly 50% of all specialty injectables are still administered to plan members in their physicians’ offices via the traditional buyand-bill method, 25% are now administered in the outpatient setting and 15% in the home health setting.3 The trend of delivering provider-administered drugs outside of the office is increasing, as facilities develop accountable care organizations.3 Some payers, working in conjunction with pharmacy benefit managers, may maintain provider office administration but eliminate

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Table 1 Spending and Utilization per 1 Million Lives, by Site of Service for the Top 10 Medical Injectables Percent of cost ($US) per claim Other (ie, ESRD and clinics)

Hospital Brand name

Home infusion/SPP

Medical office

Percent Percent Percent Percent Ranking 2009 2010 change 2009 2010 change 2009 2010 change 2009 2010 change

Remicade

1

32

34

6

32

26

–21

18

20

7

17

18

3

Avastin

2

38

40

6

40

40

1

9

8

–16

13

12

–9

Neulasta

3

25

26

5

39

33

–21

20

25

18

16

17

7

Rituxan

4

26

26

0

36

32

–10

23

24

6

16

18

11

Herceptin

5

23

24

4

36

32

–12

30

31

4

12

13

14

Lucentis

6

17

12

–38

37

33

–11

23

27

14

23

28

19

Taxotere

7

28

29

2

37

29

–28

19

24

21

15

18

18

Advate

8

38

50

24

37

13

–195

15

13

–15

10

25

145

Gammagard

9

24

29

19

26

18

–48

28

27

–4

22

26

17

Eloxatin

10

26

28

9

36

29

–25

22

24

10

16

18

14

ESRD indicates end-stage renal disease; SPP, specialty pharmacy provider. Adapted from ICORE Healthcare. Medical Pharmacy & Oncology Trend Report. © 2011. Used with permission.

the physicians’ ability to buy and bill, by mandating that drug acquisition be routed through the specialty pharmacy. However, with acquisition costs through the specialty pharmacy being 17% higher, on a weighted average basis, than those in the provider’s office, this strategy is now viewed as leading to increased costs.3 Furthermore, when drugs are shipped to the provider’s office rather than taken from the provider’s buy-and-bill stock, waste can occur (eg, because patients are subsequently being switched to alternate therapies, are incapable of tolerating the product, or are enrolled in hospice programs). Beyond higher costs at the plan level for drug acquisition outside of the buy-and-bill strategy, facility administration of specialty drugs may also come at a higher cost to patients, accompanied by a potential decline in quality of care. In addition to the inconvenience of having to visit another site outside of their providers’ offices, patients receiving their specialty therapeutics in the outpatient setting often have to deal with scheduling difficulties, wait times, and cumbersome hospital and standardized protocols. These complications may ultimately affect patient quality-of-care issues, such as nonadherence, as members face barriers to hassle-free pharmaceutical delivery. Furthermore, when providers who would otherwise be

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administering specialty drugs in their own offices are denied payment as a result of a change in distribution channel, that opportunity for direct patient contact and the continuity—and therefore quality—of care for members may potentially be disrupted.

Benefit Design Similar to efforts targeting the drug distribution channel, the use of benefit design as a means of managing specialty injectables has the potential to generate both harm and good within the system. Although removing cost-related barriers from the patient results in expanded access and/or adherence to evidence-based therapy, plan members who are not influenced by cost-sharing considerations have no incentive to be “smart shoppers” when it comes to their healthcare. Conversely, when cost-sharing parameters are so prohibitive that patients are financially unable to procure necessary treatment, payers have ultimately failed in their mission to provide quality healthcare. In 2011, 43% of plans required neither a copay nor coinsurance from members for medical injectables, and 27% of plans required coinsurance only.3 Copay is a less common strategy for specialty therapies, being the sole requirement for medical injectables by 20% of plans.

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Only 10% of plans required coinsurance and a copay from their members for specialty therapeutics.3 Smaller managed care organizations tend to use less cost-sharing, with 64% of plans with <500,000 members requiring neither a copay nor coinsurance from the patient, and with no plans of this size requiring both.3 Still, more aggressive cost-sharing on specialty drugs for members appears to be on the rise overall. Regardless of a plan size, the weighted mean coinsurance for medical injectables among payers increased from 20% in 2011 to an estimated 22% in 2012, whereas the average copay amount increased from between $45 and $46 in 2011 to an estimated $64 in 2012.3 Aside from the cost-sharing component of benefit design, genomic testing and preventive and palliative care programs offer other opportunities for managing specialty drug utilization, specifically for oncology therapies. As a means of eliminating unnecessary prescribing of costly agents to patients who will receive no therapeutic benefit from these medications, genomic tests for socalled personalized medicines are available for a select number of targeted biologics. Among the available tests, HER2 and KRAS analyses have experienced the greatest uptake, by 84% and 82% of plans in 2011, respectively.3 Likewise, the vast majority of plans in 2011 (83%) had HEDIS (Healthcare Effectiveness Data and Information Set) cancer screening/prevention programs in place.3 Recognizing the potential for inappropriate utilization of oncology therapies near the end of life, the majority of payers (55%) have also incorporated palliative care programs, and approximately half (53%) of them are covered under the general medical benefit.3

Utilization Management Initiatives Furthering efforts to promote the use of “the right therapy for the right patient at the right time,” utilization management initiatives are also used to encourage evidence-based prescribing. Although prior authorization (PA) immediately comes to mind when considering these measures, a simple “yes” or “no” based on clinical criteria is just the tip of the iceberg. Evolving from conventional PA interventions, modern utilization management measures can take myriad forms, ranging from straightforward step edits to intensive case management. Regardless of the model, 74% of plans use some form of utilization management for provider-administered injectables.3 The prevalence of utilization management varies according to therapeutic class, with PA being the most common for biologic RA therapies (63%), IVIG (60%), ESAs (58%), and chemotherapy (58%).3 Case management is most frequently used for IVIG (46%) and hemophilia therapies (49%), and step edits are the most com-

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mon for biologic therapies for RA (21%).3 The prevalence of utilization management tools by class is outlined in Table 2.3 These utilization management techniques vary in terms of scope and have, therefore, also yielded varying results for payers. Looking specifically at PA—one of the simplest forms of utilization management—some criteria are universal (eg, FDA indication applies to 100% of covered lives) or nearly universal (eg, compendia listing applies to 85% of covered lives).3 Other criteria are less common but remain prevalent, such as prior therapy failure (78%) and the dose-to-weight approach in therapeutic range for indication (61%).3 The consistency across plans in terms of implementing PA criteria is likely a result of the proven and wellestablished use of this form of utilization management among a high proportion of health plans.3 Conversely, fledgling utilization management initiatives, such as clinical pathways, are less common and have more variable results. Based on consensus therapeutic guidelines established by the National Comprehensive Cancer Network, clinical pathways are more narrow and prescriptive and allow for active, cliniciandriven management of treatment recommendations.7 The theoretical end result of these initiatives is improved quality of care, with a noticeable reduction in therapeutic variation in clinical practice. Still, despite several implementations among health plans nationwide, clinical pathways programs have so far only yielded subjective data to support their effectiveness and utility in clinical practice, and only 15% of payers with such a program report being satisfied with the results.8 For example, a recent study from 8 practices in the US Oncology network reported that annual outpatient costs for patients with non–small-cell lung cancer who were treated according to pathways protocols were 35% lower than those of patients treated off pathway, with no difference in 12-month overall survival.9 However, although retrospective costs were less for patients treated according to a pathway versus those who were off pathway, this was driven by the fact that many off-pathway patients were given ineffective and costly third- through sixth-line therapies, and this type of inappropriate prescribing can be easily managed through PA.9 Moreover, the study was not designed to demonstrate if pathways are capable of reducing or eliminating third-line (17% of off-pathway patients vs 1% of pathway patients) and fourth- through sixth-line treatment (15% of off-pathway patients vs 0% of pathway patients), which—as stated earlier—is likely the key driver of the higher costs.9 This latter component of the data suggests that the value of pathways lies in reducing unnecessary care in

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36

28

49 4

49

63

49

23

Colonystimulating agents

Biologic response modifiers (eg, Orencia, Remicade)

Hemophilia

Chemotherapyinduced nausea and vomiting

1

34

31

30

32

42

28

5

29

30

7

36

8

30

14

1

27 43

21

3

27

42

5

3

1 42

4

34

NCCN indicates National Comprehensive Cancer Network; PA, prior authorization. Adapted from ICORE Healthcare. Medical Pharmacy & Oncology Trend Report. Š 2011. Used with permission.

37

58

Chemotherapy

58

41

60

Intravenous immunoglobulin

Erythropoietinstimulating agents

46

PA, %

Therapeutic class

10

0

4

0

10

1

0

20

0

28

8

42

61

29

43

36

43

36

37

10

40

4

10

3

13

3

2

3

Case Disease Clinical pathway Differential Step edit Failure of NCCN Formulary guidelines, reimbursement, requirements, generic first, guidelines, presence, None, management, management, % % % % % % % % %

Table 2 Prevalence of Utilization Management Tools, by Therapeutic Class

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end-of-life situations, which has been achieved through simpler authorization and palliative care interventions. Further evaluation is necessary to determine the precise role that clinical pathways play in utilization management programs.

Operational Improvements Operational improvements, such as postclaim edits, represent the final means by which payers have managed specialty drug utilization and unit cost. Although medical claims data are not as â&#x20AC;&#x153;cleanâ&#x20AC;? (ie, error-free) as pharmacy claims data, these interventions have demonstrated promise as plan stakeholders become increasingly savvy about identifying and sorting the necessary information. In 2011, claims reviews conducted to monitor appropriate dosing regimens overall (54%), as well as appropriate dosing with weight-based medications (50%), were employed by plans representing at least half of the covered lives, with FDA label indications (46%) and adherence to treatment guidelines (44%) also being frequently targeted.3 Furthermore, plans representing only 30% of covered lives were not conducting edits. Nevertheless, although existing edit tools may capture severe outliers, for most plans there remains a paucity of detailed content necessary for optimizing the opportunities for improvement with this form of specialty drug management. Outside vendors with the ability to integrate medical and pharmacy claims data, as well as the technology to sort and analyze the data in a manner that produces useful results, provide an immediate solution to this problem. A Medical Pharmacy Management Approach As a function of high cost and administrative complexity, specialty drug management represents a pressing concern and top priority for health plan sponsors and stakeholders. Although few will deny the scope of the problem, the variable success of management interventions to date indicates that some solutions have limited effect. Limits in data capture can certainly account for some of the challenge; for example, cancer stage is not included in payer claims data or provider claims submission, often necessitating precertification to capture such data elements. Although all of these specialty pharmaceutical management interventions offer promise in different capacities, various initiatives should be applied in concert to maximize savings and improvements in quality of care. Modifications to provider reimbursement, for example, have led some dispensing physicians to choose highercost therapies to generate greater practice revenue. In extreme cases where reimbursement has become so unfavorable that providers can no longer afford to administer

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drugs in their offices, members are referred to the hospital or to outpatient facilities, where drug and drug administration costs are generally higher and patient care is fragmented; for example, the prescribing provider and the administering provider can be at different sites of service. Benefit designs with increased cost-sharing, often used as a method for managing the cost of care by the plan sponsor, can manifest out-of-pocket costs prohibitive to necessary treatment. Tried and true utilization management techniques, such as PA, remain a key piece of the puzzle, but these measures must be applied in a clinically sound manner, lest they become an obstacle to effective, evidencebased prescribing. Furthermore, newer utilization management initiatives, such as clinical pathways, may be conceptually intriguing but require buy-in from providers with diverse practice patterns for the treatment of specific diseases. Taking all of these factors into consideration, an appropriate approach should integrate effective components from the specialty pharmaceutical management interventions discussed above to improve the quality of care and to control costs associated with specialty drugs on behalf of payers. Significant specialty drug management expertise and access to benchmarking data serve as the foundation of such an approach. A successful medical pharmacy management strategy should include a combination of interventions, such as formulary management and rebate contracting, clinical audits on targeted products through National Drug Codes and J-codes, and guiding more intensive professional intervention with severely ill patients via case managers within the plan. Regardless of the specific approach, a medical pharmacy management strategy begins with integrated claims data, which are then leveraged to make precise and informed decisions regarding reimbursement, site of service, benefit design, and/or utilization management that can be executed internally or even carved out when necessary. As plans become increasingly sophisticated, they will strive to integrate traditional pharmacy with selfadministered and provider-administered specialty therapies. This integration allows for a comprehensive approach that is tailored to the unique and specific needs of the evolving specialty market, which affords payers the ability to manage complex drug management scenarios, such as oral versus infused chemotherapy, and steppedcare programs for diseases such as RA across all benefits. When developing a medical pharmacy management strategy, it is critical to note that the physician buy-andbill strategy continues to be the most efficient method of minimizing waste and taking advantage of the lowest acquisition costs for drugs. As such, a well-thought-out

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approach promotes the use of physician office administration as the most cost-effective site of care for oncology, rheumatology, and other patients receiving infused drugs. Another component of a comprehensive and customizable approach includes the establishment of therapeutic interchange protocols when several drugs are available to treat a particular condition. Through these interventions, providers are informed and encouraged to initiate therapy with the least costly and highest-quality alternative therapy before moving on to other more costly treatments. Results from such a specialty drug management program demonstrate that this comprehensive approach can reduce the total therapy cost for the patient, while maintaining or improving the overall quality of care.10 Specifically, payers integrating the program have saved an average of $17 million per 1 million covered lives.10 Approximately 33% of this savings stemmed from fraud and error prevention, another 33% resulted from utilization management, and the final 33% was realized through formulary and drug mix management.10 This particular strategy promotes physician choice, while also ensuring that all individual care is within nationally accepted clinical guidelines as published by a variety of independent organizations.10 Web-based systems are often used for a majority of the drug authorizations and have been rated favorably for provider satisfaction and ease of use by physician offices, which benefit from minimized disruptions in workflow.10 Furthermore, this type of claims management and editing technology brings the same proven techniques utilized in pharmacy benefit management to the management of drugs billed under the medical benefit, which reduces overuse, overbilling, errors, and outright fraud.10

Conclusions Considering the complex and interrelated processes faced by plan sponsors in the specialty pharmaceutical domain, it has become apparent that simple, one-dimensional solutions will not adequately address the alarming rate at which costs are rising, while at the same time maintaining or improving quality of care. In fact, among the diverse array of management techniques used by plan sponsors for medical injectables, many have even been counterproductive in that they ultimately lead to further increase in overall costs and/or declining quality of care. At least part of the reason behind this suboptimal management to date is the fact that plan sponsors do not rec-

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ognize all of the factors influencing the specialty drug trend, including unintended consequences, and/or they are ill-equipped for monitoring and characterizing the use of these products within their own member populations and provider networks. To overcome these challenges, a comprehensive approach to specialty injectable management is warranted. Furthermore, before implementing initiatives that address preferred agents, reimbursement, distribution channel, benefit design, utilization, and claims data, a thorough assessment of unique plan characteristics in each of these categories is necessary. In the management of specialty pharmaceuticals, knowledge is truly power, and the level of data collection and assessment in this capacity will invariably determine the success of these interventions. After plan-specific needs have been defined, a unique management approach can be carefully constructed to combat inappropriate utilization and unmitigated spending on several fronts. Ultimately, the future of specialty management lies in the ability to integrate all drugs, paid under any benefit, and administered at any site of service. â&#x2013; Author Disclosure Statement Mr Jacobs and Dr Johnson have reported no conflicts of interest.

References 1. Medco. 2011 Drug Trend Report. Healthcare 2020: fast forward to the future. Med Benefits. 2011;28:1-2. 2. Express Scripts. 2010 Drug Trend Report. April 2011. www.express-scripts.com/ research/research/dtr/archive/2010/dtrFinal.pdf. Accessed July 31, 2012. 3. ICORE Healthcare. Medical Pharmacy & Oncology Trend Report. 2nd ed. 2011. www.icorehealthcare.com/media/439145/icore_trend%20report_2011.pdf. Accessed July 31, 2012. 4. US Food and Drug Administration. Guidance for industry on biosimilars: Q & As regarding implementation of the BPCI Act of 2009. February 2012. www.fda.gov/ Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm259797.htm. Accessed July 31, 2012. 5. Howell P. How much cheaper will biosimilars be? March 2, 2012. www.fiercepharma. com/story/how-much-cheaper-will-biosimilars-be/2012-03-02. Accessed July 31, 2012. 6. Community Oncology Alliance. Community Oncology Cancer Care Practice Impact Report. March 31, 2011. http://communityoncology.org/UserFiles/files/ 87f3205e-ee73-4b03-85fb-094870cc430d/COA%20Community%20Oncology %20Practice%20Impact%20Report%203-31-11(1).pdf. Accessed July 31, 2012. 7. National Comprehensive Cancer Network. NCCN guidelines for the treatment of cancer by site. www.nccn.org/professionals/physician_gls/f_guidelines.asp#site. Accessed August 2, 2012. 8. New control techniques on the horizon for payer oncology management [press release]. Millburn, NJ: The Zitter Group; April 6, 2012. www.zitter.com/download/ New%20Control%20Techniques%20on%20the%20Horizon%20for%20Payer%20 Oncology%20Management.pdf. Accessed July 31, 2012. 9. Neubauer MA, Hoverman JR, Kolodziej M, et al. Cost effectiveness of evidencebased treatment guidelines for the treatment of nonâ&#x20AC;&#x201C;small-cell lung cancer in the community setting. J Oncol Pract. 2010;6:12-18. 10. Magellanâ&#x20AC;&#x2122;s Medical Pharmacy Solutions product manages specialty drug costs against rising trends [press release]. Avon, CT: Magellan Health Services; May 16, 2011. http://ir.magellanhealth.com/releasedetail.cfm?ReleaseID=577917. Accessed July 31, 2012.

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STAKEHOLDER PERSPECTIVE Managing Medical Benefit Drugs Under Specialty Pharmacy: The Next Critical Challenge for Managed Care The tremendous increase in the cost of specialty pharmaceuticals is a significant concern for health plan pharmacy managers. As discussed in the article by Jacobs and Johnson, the reasons for this growth include new product approvals, price increases, increased utilization, and the overall share of the market that these products represent. Historically, health plans have been very effective at using utilization management tools for traditional, small-molecule pharmaceuticals, and pharmacy benefit managers have successfully assisted plans in this process. The use of prior authorizations, step edits, quantity limits, treatment guidelines, and benefit designs with increasing patient out-of-pocket (OOP) costs have effectively helped to manage drug spending and drug trends in many therapeutic categories. Traditionally, drugs covered under the medical benefit were not managed by pharmacy. PHARMACY/MEDICAL DIRECTORS: The growth in specialty pharmacy drug spending over the past few years has been unprecedented; however, this growth has been masked by the significant launches of a number of blockbuster generic agents, including atorvastatin, clopidogrel, and losartan. An evaluation of the specialty drug distribution costs compared with the medical benefit drug buy-and-bill rates based on average sales price (ASP) usually favors the ASP pricing over the specialty pharmacy pricing. This supports maintaining the buy-and-bill methodology as the primary reimbursement approach for medical benefit drugs. A new challenge is to effectively apply utilization management methods to the large-molecule specialty drugs that are managed under the medical benefit. The significant number of drugs in the pipeline, including more than 90 agents for orphan diseases, as reported by the Pharmaceutical Research and Manufacturers of America, as well as 900 drugs for cancer,1 will present unique challenges as plans try to manage this tidal wave of potential new agents. The promise of biosimilars is encouraging as a means for price relief for select drugs in the future. The recent US Food and Drug Administration guidance on the potential approval process for biosimilars2 provides manufacturers some idea on the requirements for submission and approval. The anticipated price discounts will not mirror the small molecules, where a decrease of 80% to 90% off the price of the reference drug is very common. I disagree with the current consensus that the discounts

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on biosimilars will be in the 10% to 20% range,1 because this will allow the innovator companies to simply contract to retain the existing business, and health plans could block the offering of biosimilars and avoid the challenge of driving utilization of biosimilars. Rather, I expect the discounts to be in the 30% to 50% range, to encourage plans to adopt and aggressively promote biosimilar agents. Additional challenges faced by health plan pharmacy managers include the ability to effectively track utilization of medical and pharmacy claims and target appropriate interventions to control costs. Plans need to develop robust reporting capability to effectively monitor the impact of interventions and detect untoward consequences, including site of care shifts or product selection changes that promote increased profits or decreased costs to the physician practices, while increasing overall health plan drug costs. Patient cost-sharing is another trend that will benefit the plan management strategies, by engaging the patient in the product selection discussion, when appropriate, with OOP costs that will vary by product, based on formulary tiers or on different coinsurance rates on a branded agent compared with a preferred agent, generic product, or an approved biosimilar. The role of diagnostic tests, biomarkers, and personalized medicine holds promise for improved patient outcomes based on targeted treatment approaches. In addition, the opportunity for outcomes-based contracting increases with the ability to target patients and predict outcomes more accurately for specific therapies. The successful plan managers must use a comprehensive approach to the management of medical injectables that will rely heavily on a strong information technology infrastructure for reporting and claims management, incorporation of diagnostics into treatment programs, maximizing existing and new utilization management tools, and encouraging manufacturers to engage in outcomes-based contracting on their products. James T. Kenney, Jr, RPh, MBA Pharmacy Operations Manager Harvard Pilgrim Health Care 1. PhRMA. Medicines in development. 2012. www.phrma.org/research/new-medicines. 2. US Food and Drug Administration. Guidance for industry on biosimilars: questions and answers regarding Implementation of the Biologics Price Competition and Innovation Act of 2009. February 2012. www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/ Guidances/UCM273001.pdf.

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CLINICAL

Original research

Anticoagulant Use for Prevention of Stroke in a Commercial Population with Atrial Fibrillation aarti a. Patel, PharmD, MBa; Barb lennert, rn, Bsn, MaOM; Brian Macomson, PharmD; Winnie W. nelson, PharmD; gary M. Owens, MD; samir h. Mody, PharmD, MBa; Jeff schein, DrPh, MPh Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and patients with AF are at an increased risk for stroke. Thromboprophylaxis with vitamin K antagonists reduces the annual incidence of stroke by approximately 60%, but appropriate thromboprophylaxis is prescribed for only approximately 50% of eligible patients. Health plans may help to improve quality of care for patients with AF by analyzing claims data for care improvement opportunities. Objectives: To analyze pharmacy and medical claims data from a large integrated commercial database to determine the risk for stroke and the appropriateness of anticoagulant use based on guideline recommendations for patients with AF. Methods: This descriptive, retrospective claims data analysis used the Anticoagulant Quality Improvement Analyzer software, which was designed to analyze health plan data. The data for this study were obtained from a 10% randomly selected sample from the PharMetrics Integrated Database. This 10% sample resulted in almost 26,000 patients with AF who met the inclusion criteria for this study. Patients with a new or existing diagnosis of AF between July 2008 and June 2010 who were aged ≥18 years were included in this analysis. The follow-up period was 1 year. Demographics, stroke risk level (CHADS2 and CHA2DS2-VASc scores), anticoagulant use, and inpatient stroke hospitalizations were analyzed through the analyzer software. Results: Of the 25,710 patients with AF (CHADS2 score 0-6) who were eligible to be included in this study, 9093 (35%) received vitamin K antagonists and 16,617 (65%) did not receive any anticoagulant. Of the patients at high risk for stroke, as predicted by CHADS2, 39% received an anticoagulant medication. The rates of patients receiving anticoagulant medication varied by age-group—16% of patients aged <65 years, 22% of those aged 65 to 74 years, and 61% of elderly ≥75 years. Among patients hospitalized for stroke, only 28% were treated with an anticoagulant agent in the outpatient setting before admission. Conclusions: Our findings support the current literature, indicating that many patients with AF are not receiving appropriate thromboprophylaxis to counter their risk for stroke. Increased use of appropriate anticoagulation, particularly in high-risk patients, has the potential to reduce the incidence of stroke along with associated fatalities and morbidities.

A

trial fibrillation (AF) is the most common clinically significant cardiac arrhythmia, diagnosed in approximately 1% of the general population.1 It is estimated that AF currently affects more

Barb Lennert

Stakeholder Perspective, page 297

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than 2 million people in the United States and more than 4 million across the European Union, with the number of US patients with AF estimated to increase 2.5-fold by the year 2050.1,2

Dr Patel is Associate Director, Health Economics and Outcomes Research, Janssen Scientific Affairs, LLC, Raritan, NJ; Ms Lennert is Senior Director, Xcenda, LLC, Palm Harbor, FL; Dr Macomson is Principal Liaison, Health Economics and Outcomes Research, Janssen Scientific Affairs, LLC, Raritan, NJ; Dr Nelson is Director of Health Economics and Outcomes Research, Janssen Scientific Affairs, LLC, Raritan, NJ; Dr Owens is President, Gary Owens Associates, Glen Mills, PA; Dr Mody is Director of Health Economics and Outcomes Research, Janssen Scientific Affairs, LLC, Raritan, NJ; and Dr Schein is Senior Director, Health Economics and Outcomes Research, Janssen Scientific Affairs, LLC, Raritan, NJ.

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KEY POINTS ➤

Atrial fibrillation (AF) is responsible for approximately 20% of all strokes; stroke is the third most common cause of US deaths. Current guidelines for stroke prevention recommend thromboprophylaxis for all patients with AF who are at high risk for stroke. Appropriate thromboprophylaxis is the mainstay of stroke prevention, resulting in approximately 60% ischemic stroke risk reduction. In this claims data analysis, however, 65% of patients with AF did not have claims for anticoagulant therapy; the rate was only slightly lower (61%) among patients at high risk for stroke, with only 39% receiving anticoagulation therapy. Age played some role in the rate of anticoagulation use: only 16% of patients with AF under age 65 years had claims for an anticoagulant agent compared with 22% for those aged 65 to 74 years and 61% among those aged ≥75 years. These findings echo previous findings in the medical literature, suggesting a significant underutilization of anticoagulation therapy in people with AF. Although the cost of treating AF is significant— amounting to an estimated $6.65 billion direct cost in 2005—this amount is dwarfed by the treatment of stroke, which in 2010 was estimated at $73.7 billion for direct and indirect costs. Quality of care in this patient population can be improved by using software designed to analyze claims data to identify practice patterns and ways to improve treatment adherence.

AF is a powerful independent risk factor for stroke. Patients with AF are estimated to have a 5-fold greater risk for stroke than those without AF,3 and AF is thought to have a causative role in approximately 20% of all strokes.4 The individual stroke risk may be estimated using the CHADS2 (C = congestive heart failure, H = hypertension, A = age, D = diabetes, and S2 = stroke/transient ischemic attack) or CHA2DS2-VASc (C = congestive heart failure/left ventricular dysfunction, H = hypertension, A2 = age [≥75 years], D = diabetes, S2 = stroke/transient ischemic attack, V = vascular disease, A = age 65-74 years, and Sc = sex category) classification schemes; classification is based on patient characteristics, with higher scores corresponding to a higher risk for stroke.5,6 The prevalence of AF rises with increasing age. In patients aged <55 years, the prevalence is approximately 0.1%, but this increases to 9.0% in persons aged ≥80 years.1 The cost of treating AF places a significant bur-

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den on the healthcare system.7 In 2005, the annual total direct cost of treating patients with AF was estimated to be $6.65 billion.8 This figure, however, is dwarfed by the costs of treating stroke; in 2010, the combined direct and indirect cost of stroke in the United States was estimated to be $73.7 billion.9 The mean individual lifetime cost of ischemic stroke in the United States is estimated to be $140,048.9 Thromboprophylaxis is the mainstay of stroke prevention in patients with AF. Based on clinical practice guidelines published by the American College of Cardiology, the American Heart Association, the American College of Chest Physicians, and the European Society of Cardiology, patients with AF should generally receive an anticoagulant (usually a vitamin K antagonist) or antiplatelet regimen (usually acetylsalicylic acid), depending on their risk for stroke and serious bleeding.2,7,10-12 Long-term therapy with a vitamin K antagonist can reduce the risk for stroke by between 62% and 68% in patients with nonvalvular AF.13,14 Despite the availability of appropriate prophylaxis, thromboprophylaxis is prescribed for only approximately 50% of all eligible patients with AF.15 There is a clear need to improve the quality of care for these patients. Current quality measures for providers of treatment for AF broadly assess adherence to 3 primary areas of stroke prevention16: 1. The use of pharmacologic therapy 2. Assessment of risk factors for thromboembolism and disease progression 3. Maintenance of anticoagulant therapy within recommended international normalized ratios (INRs). Health plans may be able to improve quality of care by using available software to analyze the plan’s claims data; the results may help decision makers identify practice patterns among plan clinicians and members, as well as potential opportunities to improve treatment by identifying members’ stroke risk level, those not receiving appropriate, that is, guideline-based, thromboprophylaxis, and/or patients who are not being properly monitored for bleeding risk while taking an oral anticoagulant. Once identified, health plans can design patient and provider quality improvement interventions aimed at improving care for these at-risk populations. The purpose of this study was to analyze pharmacy and medical claims data using AF-specific software to determine the risk for stroke and guideline-recommended use of anticoagulant therapy in a population of patients with a new diagnosis of AF.

Methods Data Source The claims data were obtained from the PharMetrics

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Integrated Database from July 2008 to June 2010 (IMS Health, Inc; Danbury, CT). This deidentified database includes medical and pharmacy claims of patients enrolled by commercial insurers in the United States. The PharMetrics Integrated Database includes inpatient and outpatient claims, diagnoses, and procedures based on the International Classification of Diseases, Ninth Revision (ICD-9); Current Procedural Terminology, Fourth Edition codes; and retail and mail-order pharmacy claims in excess of 70 million individuals from more than 100 health plans.17

Study Design and Tools This study is a descriptive, retrospective claims analysis conducted using the Anticoagulant Quality Improvement Analyzer software, a condition-specific software tool designed to evaluate population characteristics, population health risks, and appropriateness of medication use by allowing health plans to upload their pharmacy and medical claims data via a simple point-andclick method. A randomly selected 10% sample of patients from the PharMetrics Integrated Database was analyzed in this study by using this automated Health Insurance Portability and Accountability Act–compliant software tool to produce results for a series of predetermined and user-defined measures and to generate actionable, patient/prescriber-level, overall sample-specific reports. A 10% sample of this database was deemed sufficient to provide an appropriate number of patients to accurately represent treatment patterns within the population of patients with AF; indeed, nearly 26,000 patients with AF who met the inclusion criteria for this study were identified in this 10% sample. Inclusion Criteria Patients were included in the analysis if they met all of the following inclusion criteria: • Their information was in the PharMetrics Integrated Database between July 2008 and June 2010 • They had a follow-up period of 12 months after AF diagnosis • They were aged ≥18 years • They had ≥1 primary or secondary diagnoses of AF • Their pharmacy and medical claims were both recorded in the database. Variable Descriptions Comorbidities were identified using ICD-9 Clinical Modification diagnosis codes (Table 1).18 Measurements of stroke risk were based on the CHADS2 and CHA2DS2-VASc scoring systems. Using the CHADS2 system, each patient was assigned 1 point for each of the following factors: presence of con-

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Table 1 Comorbid Conditions of Interest Comorbidity

N (%)

Stroke

2743 (11)

Hypertension

16,390 (64)

Diabetes

7015 (28)

Heart failure

6457 (25)

Acute myocardial infarction

795 (3)

Coronary heart disease

8688 (34)

Arrhythmias other than atrial fibrillation

6933 (27)

Source: Reference 18.

gestive heart failure (CHF), presence of hypertension (ie, systolic blood pressure [BP] >160 mm Hg), age ≥75 years, and presence of diabetes. Two points were assigned for a history of stroke or transient ischemic attack (TIA). The CHA2DS2-VASc system is another risk factor– based schema for predicting stroke and thromboembolism in patients with AF. It incorporates additional risk factors that are not included in CHADS2. In a validation study, CHA2DS2-VASc was found to be superior to CHADS2 in differentiating patients with high-risk AF from those with low-risk AF.6 Using the CHA2DS2-VASc system, each patient in the present study was assigned 1 point for each of the following factors: the presence of CHF/left ventricular dysfunction; age 65 to 74 years; presence of hypertension (systolic BP >160 mm Hg), diabetes, or vascular disease (coronary artery disease, acute myocardial infarction, peripheral artery disease, aortic plaque); and female sex. Two points were assigned for each of the following factors: age ≥75 years and history of stroke, TIA, and thromboembolism. Patients with AF were subsequently assigned to 1 of the following categories based on their risk factors for stroke, using both stroke risk assessment scoring systems: low risk (0 points), moderate risk (1 point), or high risk (≥2 points).

Outcomes Prescribing patterns and outcomes were assessed during the 1-year period after the first occurrence of the diagnosis of AF in the study timeframe. The outcomes based on medical and pharmacy claims that were investigated included anticoagulant use, anticoagulant use by stroke risk score and age, and outpatient anticoagulant use in those hospitalized for stroke. To investigate the appropriate use of anticoagulants, levels of use and time to first gap of ≥60 days in anticoagulant therapy were assessed.

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Anticoagulant use categorized by stroke risk was assessed by classifying patients into low-, moderate-, and highrisk categories as defined by CHADS2 score. In addition, anticoagulant use by age was assessed in patients aged ≥75 years, 65 to 74 years, and <65 years. In patients who were hospitalized for stroke, the rate of anticoagulant use in the outpatient setting was also investigated.

was 71.6 years (74.3 for female patients and 69.7 for male patients). Using the CHADS2 system, the proportions of patients at low, moderate, and high risk for stroke were estimated to be 17%, 28%, and 54%, respectively. Using the CHA2DS2-VASc system, the proportions of patients at low, moderate, and high risk for stroke were estimated to be 7%, 12%, and 81%, respectively (Table 2).

Results Patient Demographics A total of 25,710 patients with AF were analyzed; 58% of the patients were male. The mean age of patients

Anticoagulant Use Among the total AF population in this study, based on claims data, 9093 (35%) patients with AF received anticoagulant treatment to reduce the risk for stroke and 16,617 (65%) did not (Table 3). Because the data used in this analysis were collected only up to June 2010, newer oral anticoagulant agents were not included. Of the 9093 patients who received an anticoagulant, 4877 (54%) had a gap of ≥60 days in therapy. The mean time from initiation of anticoagulation to interruption of therapy was 166 days.

Table 2 Patient Characteristics Demographic characteristics

Patients

All patients, N

25,710

Sex, N (%) Female

10,781 (42)

Male

14,929 (58)

Average age, yr

71.6

Female

74.26

Male

69.68

Risk score, N (%) CHADS2 Low (0)

4442 (17)

Moderate (1 point)

7313 (28)

High (≥2 points)

13,955 (54)

CHA2DS2-VASc Low (0)

1672 (7)

Moderate (1 point)

3178 (12)

High (≥2 points)

20,860 (81)

Anticoagulant Use, by Stroke Risk and Age Based on the CHADS2 scoring system, the rates of anticoagulant use in patients with AF were found to be relatively low, even in patients deemed to be at a high risk for stroke. Overall, based on claims data, only 39% of patients in the high-risk category received an anticoagulant. However, rates varied by age-group, with 16%, 22%, and 61% of patients aged <65 years, 65 to 74 years, and ≥75 years, respectively, receiving an anticoagulant. In the moderate-risk category, 39%, 40%, and 21% of patients by age stratification of <65 years, 65 to 74 years, and ≥75 years, respectively, received an anticoagulant; and in the low-risk category, 60%, 40%, and 0% of patients, respectively, received an anticoagulant (Table 3). Rate of Outpatient Anticoagulant Use in Patients Hospitalized for Stroke Based on claims data, the rate of preadmission out-

Table 3 Anticoagulant Use, by Stroke Risk and Age Patients receiving anticoagulant, by CHADS2 risk groupa

Age-group, yr <65 (N = 7952) N (%) 879 (16)

65-74 (N = 6736) N (%) 1216 (22)

≥75 (N = 11,022) N (%) 3319 (61)

All age-groups (N = 25,710) N (%)a 5414/13,955 (39)

Moderate risk

954 (39)

992 (40)

529 (21)

2475/7313 (34)

Low risk

725 (60)

479 (40)

0 (0)

1204/4442 (27)

All risk groups

2558 (32)

2687 (40)

3848 (35)

9093/25,710 (35)

High risk

a

Percentages represent proportion of patients receiving anticoagulant therapy in that risk group.

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patient anticoagulation was low in patients who were hospitalized for stroke. Of the 616 patients who were hospitalized for stroke, 173 were treated with an anticoagulant in the outpatient setting, representing 28% of the total (Table 4).

Table 4 Outpatient Anticoagulant Use in 25,710 Patients Hospitalized for Stroke Inpatient stroke hospitalization

616 (2)

Discussion Current medical guidelines for stroke prevention recommend that all patients with AF who are at high risk for stroke receive thromboprophylaxis, unless contraindicated.2,7,11,12 Appropriate thromboprophylaxis has been shown to reduce the risk for ischemic stroke by approximately 60%.13,14 However, studies have shown that nearly 50% of patients with AF do not receive appropriate thromboprophylaxis.15,19,20 In our analysis, 65% of patients with AF captured in the PharMetrics Integrated Database did not have claims for anticoagulation therapy. Even among patients at high risk for stroke, 61% did not have a claim for an anticoagulant. Furthermore, among patients with AF who were subsequently hospitalized for stroke, 72% did not have a claim for an anticoagulant medication in the outpatient setting before hospitalization. Our findings, based on data before the availability of the newer anticoagulant agents, are consistent with the past literature, providing further evidence of the need to improve the management of AF in the outpatient setting. The ramifications of stroke can be devastating for patients and costly for health plans. Stroke is the third most common cause of death in the United States and a leading cause of long-term morbidity.3 The mean lifetime cost of ischemic stroke in the United States is estimated to be $140,048.9 AF is one of the 20 medical conditions identified by the Centers for Medicare & Medicaid Services and the National Quality Forum that impose heavy health burdens on patients and collectively account for more than 95% of Medicare’s costs.21 These figures highlight the need for improved management of AF to reduce the incidence of stroke. Several reasons explain why physicians and patients may find it challenging to manage the risk of AF-related stroke effectively. Physicians may struggle with the complexities of stratifying stroke risk in patients with AF. More than a dozen stroke risk–stratification systems for patients with AF have been proposed, based on various combinations of clinical and echocardiographic predictors, and although CHADS2 and CHA2DS2-VASc are the most frequently used systems, none has been convincingly shown to be “the best.”22 Physicians also may have concerns about cognitive and physical impairment having an impact on the decision-making process for elderly patients and may be reluctant to prescribe anticoagulants for this population.23

Untreated with anticoagulant in outpatient setting

443 (72)

Treated with anticoagulant in outpatient setting

173 (28)

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Variable

Patients, N (%)

Risk stratification necessitates an estimate not only of stroke risk but also of risk for bleeding. The risk for bleeding, risk for falls, and patients’ ability to comply with treatment also have been identified as important physician concerns that may lead to a clinical decision to limit anticoagulation therapy in the elderly.24 As the clinician considers bleeding risk, he/she must also differentiate between the likelihood of a minor bleeding event versus a major bleeding episode. Lane and Lip note that “physicians may not adhere to the guidelines because they are either not aware of them or their knowledge of them is poor.”25 They also suggest that failure to adhere to clinical practice guidelines “may be because the guidelines are deficient in terms of evidence-based information,” and physicians may feel that this limits the applicability of these guidelines to certain patients.25 Patients, as well as healthcare providers, may fail to adhere to published guidelines for anticoagulation therapy in AF. For example, we found that 54% of patients in our study had a gap in therapy of >60 days. Such treatment gaps may have numerous causes. Often, patients have a limited understanding of the value of vitamin K antagonist therapy for stroke prophylaxis, and many are unaware of the risks associated with overanticoagulation or underanticoagulation. As a result, INR monitoring visits at anticoagulation clinics are frequently missed, INR values are frequently out of range, and dose adjustments are often required, particularly in the elderly.26 In addition, treatment with a vitamin K antagonist is also often perceived as a burden on lifestyle, restricting diet, social life, career, independence, and physical activities.26 Despite the increasing prevalence of AF and related complications, there has been limited focus on quality improvement activities in outpatients. The Agency for Healthcare Research and Quality’s National Quality Measures Clearinghouse identifies 45 heart failure–specific quality measures and 71 diabetes-specific measures, but only 6 AF-related measures, all of which address stroke prevention.27 The American Recovery and Reinvestment Act of

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2009 called on the Institute of Medicine to recommend a list of priority topics in comparative effectiveness research (research designed to inform healthcare decisions by providing evidence on the effectiveness, benefits, and harms of different treatment options) that deserve federal support. AF is within the top quartile of priorities.28 The software tool used in this study offers an effective and easy-to-use method for retrospectively analyzing claims data, helping to identify patients with AF who are at high risk of stroke, and highlighting whether healthcare providers are managing that risk appropriately based on guideline recommendations. Health plans; Pharmacy & Therapeutics committees; and medical, pharmacy, and quality improvement directors may find it beneficial to use the findings generated by this software to implement targeted educational programs for patients and healthcare providers regarding the importance of stroke prevention among patients with AF and recommended guidelines to determine the need for anticoagulant prophylaxis.

Limitations There are a number of limitations to this study. First, we cannot guarantee the completeness and accuracy of the medical claims data used in this analysis. Claimsbased analyses rely on data that are used primarily for administrative (ie, billing, payment, and operations) purposes. The data do not, therefore, necessarily reflect all of the clinical variables taken into account by physicians when making treatment decisions; therefore, some clinical characteristics (eg, INR, contraindications to anticoagulant therapy) will not have been captured, and there is the potential for some patients to have been misclassified in claims data that are included in the PharMetrics Integrated Database. An assessment of bleeding risk should be part of a patient assessment before starting anticoagulation therapy. Our analysis did not include bleeding risk, resulting in a potential overestimate for undertreatment. Furthermore, the data captured in this analysis cover only a short period of patients’ medical histories; the information was limited to prescribing patterns and outcomes during the 1 year after the diagnosis of AF. The data may have omitted relevant risk-related events that occurred before the diagnosis of AF (eg, a previous stroke), and this might have led to underestimations of stroke risk scores. Another area that is not captured by the medical claims database is over-the-counter medication use. Therefore, there are no data regarding the use of aspirin. Finally, this analysis considered only patients for whom both medical and pharmacy claims data were available. Patients who had only medical or only phar-

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macy data included in the database were discounted, and this might have affected the overall results.

Conclusions Given the enormous clinical and economic impact of AF-related stroke, AF is an ideal target for quality improvement efforts. Based on medical and pharmacy claims data obtained from the PharMetrics Integrated Database, our analysis showed that 54% of patients diagnosed with AF were at a high risk of stroke according to CHADS2 criteria. Of these patients, 61% did not have a claim for anticoagulant therapy. Furthermore, among patients who were hospitalized for a new stroke, more than 70% did not have a claim for an anticoagulant agent in the outpatient setting. This claims-based analysis supports the findings seen in the past literature that many patients with AF are not receiving appropriate thromboprophylaxis to counter their risk for stroke.15,20 Anticoagulant use for the prevention of stroke in patients with AF appears suboptimal. Increased use of appropriate anticoagulation therapy has the potential to reduce the incidence of stroke, along with associated fatalities and morbidities. ■ Author Disclosure Statement Dr Patel, Dr Macomson, Dr Nelson, Dr Mody, and Dr Schein are employees of Janssen and shareholders of Johnson & Johnson; Ms Lennert is an employee of Xcenda; and Dr Owens is a consultant to Allergan, Auxilium, Biogen Idec, Boston Scientific, CardioDx, Eli Lilly, Eyetech, Genzyme, Janssen/Johnson & Johnson, and Q Pharma.

References 1. Go AS, Hylek EM, Phillips KA, et al. Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the Anticoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study. JAMA. 2001;285:2370-2375. 2. Fuster V, Rydén LE, Cannom DS, et al. ACC/AHA/ESC 2006 Guidelines for the Management of Patients with Atrial Fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines (Writing Committee to Revise the 2001 Guidelines for the Management of Patients With Atrial Fibrillation): developed in collaboration with the European Heart Rhythm Association and the Heart Rhythm Society. Circulation. 2006;114:e257-e354. 3. Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics—2011 update: a report from the American Heart Association. Circulation. 2011;123:e18-e209. 4. Marini C, De Santis F, Sacco S, et al. Contribution of atrial fibrillation to incidence and outcome of ischemic stroke: results from a population-based study. Stroke. 2005;36:1115-1119. 5. Gage BF, Waterman AD, Shannon W, et al. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA. 2001;285:2864-2870. 6. Lip GY, Nieuwlaat R, Pisters R, et al. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the Euro Heart Survey on Atrial Fibrillation. Chest. 2010;137:263-272. 7. Fuster V, Rydén LE, Cannom DS, et al. 2011 ACCF/AHA/HRS focused updates incorporated into the ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation. 2011;123:e269-e367. 8. Coyne KS, Paramore C, Grandy S, et al. Assessing the direct costs of treating nonvalvular atrial fibrillation in the United States. Value Health. 2006;9:348-356. 9. Lloyd-Jones D, Adams RJ, Brown TM, et al. Heart disease and stroke statistics—

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2010 update: a report from the American Heart Association. Circulation. 2010;121: e46-e215. 10. Macedo PG, Ferreira Neto E, Silva BT, et al. Oral anticoagulation in patients with atrial fibrillation: from guidelines to bedside. Rev Assoc Med Bras. 2010;56:56-61. 11. Camm AJ, Kirchhof P, Lip GY, et al. Guidelines for the management of atrial fibrillation: the Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC). Eur Heart J. 2010;31:2369-2429. 12. Singer DE, Albers GW, Dalen JE, et al. Antithrombotic therapy in atrial fibrillation: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th edition). Chest. 2008;133(6 suppl):546S-592S. 13. European Atrial Fibrillation Trial. Secondary prevention in non-rheumatic atrial fibrillation after transient ischaemic attack or minor stroke. EAFT (European Atrial Fibrillation Trial) Study Group. Lancet. 1993;342:1255-1262. 14. Ezekowitz MD, Levine JA. Preventing stroke in patients with atrial fibrillation. JAMA. 1999;281:1830-1835. 15. Goto S, Bhatt DL, Rรถther J, et al. Prevalence, clinical profile, and cardiovascular outcomes of atrial fibrillation patients with atherothrombosis. Am Heart J. 2008;156: 855-863,863. 16. Estes NA 3rd, Halperin JL, Calkins H, et al. ACC/AHA/Physician Consortium 2008. Clinical Performance Measures for Adults with Nonvalvular Atrial Fibrillation or Atrial Flutter: a report of the American College of Cardiology/American Heart Association Task Force on Performance Measures and the Physician Consortium for Performance Improvement (Writing Committee to Develop Clinical Performance Measures for Atrial Fibrillation) Developed in Collaboration with the Heart Rhythm Society. J Am Coll Cardiol. 2008;51:865-884. 17. IMS Health. PharMetrics Integrated Database. 2012. www.imshealth.com/portal/ site/ims/menuitem.d248e29c86589c9c30e81c033208c22a/?vgnextoid=d6952a2e232 64310VgnVCM100000ed152ca2RCRD&vgnextfmt=default. Accessed July 23, 2012.

18. Centers for Disease Control and Prevention. ICD-9-CM tabular list of diseases. 2011. www.cdc.gov/nchs/icd/icd9cm.htm. Accessed July 27, 2012. 19. Bungard TJ, Ghali WA, Teo KK, et al. Why do patients with atrial fibrillation not receive warfarin? Arch Intern Med. 2000;160:41-46. 20. Lakshminarayan K, Solid CA, Collins AJ, et al. Atrial fibrillation and stroke in the general Medicare population: a 10-year perspective (1992 to 2002). Stroke. 2006; 37:1969-1974. 21. National Quality Forum. Prioritization of high-impact conditions for healthcare performance measurement. www.qualityforum.org/projects/prioritization.aspx. Accessed November 16, 2011. 22. Goldstein LB, Bushnell CD, Adams RJ, et al. Guidelines for the primary prevention of stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2011;42:517-584. 23. Abdel-Latif AK, Peng X, Messinger-Rapport BJ. Predictors of anticoagulation prescription in nursing home residents with atrial fibrillation. J Am Med Dir Assoc. 2005;6:128-131. 24. Pugh D, Pugh J, Mead GE. Attitudes of physicians regarding anticoagulation for atrial fibrillation: a systematic review. Age Ageing. 2011;40:675-683. 25. Lane DA, Lip GY. Barriers to anticoagulation in patients with atrial fibrillation: changing physician-related factors. Stroke. 2008;39:7-9. 26. Lip GY, Agnelli G, Thach AA, et al. Oral anticoagulation in atrial fibrillation: a pan-European patient survey. Eur J Intern Med. 2007;18:202-208. 27. Agency for Healthcare Research and Quality. National Quality Measures Clearinghouse. http://qualitymeasures.ahrq.gov/. Accessed July 27, 2012. 28. Institute of Medicine. 100 Initial priority topics for comparative effectiveness research. www.iom.edu/~/media/Files/Report%20Files/2009/ComparativeEffectiveness ResearchPriorities/Stand%20Alone%20List%20of%20100%20CER%20Priorities% 20-%20for%20web.ashx. Accessed January 9, 2012.

STAKEHOLDER PERSPECTIVE The Enormous Impact of Atrial Fibrillation and Stroke on Patients, Payers, and Society The enormity of the impact of atrial fibrillation (AF) and subsequent strokes cannot be overstated. The outcomes of strokes for patients, caregivers, and payers (regardless of payment classification) are devastating. As the US population of those aged >65 years surges, now and certainly in the long-term, acute AF and the potential for stroke have enormous consequences for the individual patient and for society. SOCIETY: According to the Centers for Medicare & Medicaid Services, approximately 8.6% of Medicare recipients aged >65 years have suffered a stroke.1 The death rate for those who have had a stroke is 40.7 per 100,000 persons.1 The sheer listing of death rates does not encompass the socioeconomic, family, payer, or societal factors that are affected by cerebrovascular disease, such as the occurrence of a stroke. Therefore, it is crucial for comprehensive examinations of sophisticated computer modeling of varying components that are enhancing outcomes research to

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become more commonplace than presently is the case in the United States. Since 1999, the National Institute for Health and Clinical Effectiveness (NICE) has served as a reference and guidance bureau for assessing, guiding, and monitoring outcomes-based research pertaining to the public health in the United Kingdom.2 The NICE framework encompasses the sophistication necessary to evaluate all components of the UK National Health Service providing universal coverage for British citizens. Many stakeholders believe that a similar framework for outcomes research could provide dividends for many aspects of health conditions (ie, AF and stroke) in the United States as well. PATIENTS/CAREGIVERS: Many newer treatment options for AF and stroke prevention have recently become available. Novel oral anticoagulants have been shown to be equally as effective as warfarin, the standard treatment for decades, and the

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STAKEHOLDER PERSPECTIVE (continued) newer agents do not require monitoring,3 thereby increasing the prescribing options for stroke prevention in patients with AF, as well as decreasing the long-term costs that are associated with the treatment of patients with AF. As noted, the long-term healthcare costs of stroke and its sequelae are substantial. With the expected increase in the Medicare population over the coming decades, there is an urgent need for an enhanced emphasis on the necessity for effective preventive care afforded by appropriate treatments for AF to avoid the long-term costs and impacts on patients, caregivers, and families.4 PAYERS/PROVIDERS: From a quality-improvement perspective, as well as from an enhanced opportunity for advanced assessment of health outcomes, the techniques, research design, and the important data derived from the present study by Dr Patel and colleagues provide a model template for many researchers, stakeholders, and payers. All those who are involved in this condition can see the path to providing better-

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informed treatment options for patients with AF as a crucial benefit from studies such as the one presented in this article. The avoidance of the enormous impact of stroke as a consequence of untreated or undertreated AF is an important consideration for so many who have a stake in this condition. Jack E. Fincham, PhD, RPh Professor, Pharmacy Practice and Administration University of Missouri-Kansas City Division of Pharmacy Practice and Administration Adjunct Professor of Health Administration The Bloch School of Management Kansas City, MO 1. US Department of Health and Human Services, National Center for Health Statistics. Health, United States, 2011: with special feature on socioeconomic status and health. www.cdc.gov/nchs/data/hus/hus11.pdf. Accessed August 13, 2012. 2. National Institute for Health and Clinical Effectiveness (NICE). NICE quality standards. www.nice.org.uk/aboutnice/qualitystandards/qualitystandards.jsp. Accessed August 13, 2012. 3. Edwards D, Harris K, Mant J. Management of patients with atrial fibrillation at high risk of stroke: current treatment options. Res Rep Clin Cardiol. 2012;3:35-47. 4. Lee WC, Christensen MC, Joshi AV, Pashos CL. Long-term cost of stroke subtypes among Medicare beneficiaries. Cerebrovasc Dis. 2007;23:57-65.

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Cost Management through Care Management: A Perspective on Choosing the Right Specialty Pharmacy Partner, PART 1 Michael Einodshofer, RPh, MBA, and Stephen Kansler Mr Einodshofer is Director of Utilization Management, and Mr Kansler is Vice President, Walgreens Specialty Pharmacy, Pittsburgh, PA

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pecialty pharmaceuticals are quickly commanding a growing share of prescription market share dollars and consequently a greater amount of attention from payers. It is becoming increasingly important for payers to fully understand the nuances of cost control within the specialty pharmacy space before developing a contracting and formulary strategy for specialty pharmaceuticals. Although the contractual unit cost (eg, an average wholesale price [AWP] discount) established between a specialty pharmacy and a payer is still an important aspect of managing specialty pharmacy spending, the unit cost should not be used in isolation as a strategy to manage specialty pharmacy costs. From our perspective as one of the largest specialty pharmacies in the United States, the following 4 questions regarding specialty pharmacy competencies can influence a payer’s specialty drug costs: 1. How does the specialty pharmacy encourage patient compliance, minimize side effects, and educate each

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individual patient who is prescribed a specialty drug? 2. How does the specialty pharmacy minimize the “cost to treat” each individual patient? 3. Does the specialty pharmacy offer a competitive unitprice discount? 4. What solutions does the specialty pharmacy offer to manage drug costs within the medical benefit? In this article we address the first 3 questions. In our next article we will provide a thorough discussion on managing drug trends within the medical benefit.

Defining a Specialty Drug An industry-standard, consistent definition for a specialty drug has yet to be universally accepted. According to an EMD Serono survey of payers, the determining factors defining a specialty drug include high cost, requiring special handling, availability from certain pharmacies only (ie, limited distribution), requiring ongoing assessment of response, treating a rare disease, and requiring

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the monitoring of side effects.1 The route of administration of a drug is typically immaterial, because specialty drugs can be self- or provider-administered. Although this definition has yet to evolve into an industry-accepted standard, by and large payers agree on the assignment of the “specialty” status for most drugs. Some disagreement can be found in therapeutic areas such as transplantation and HIV medications, which some payers do not consider specialty drugs, because these medications are often dispensed from retail pharmacies. The specialty drugs that are on the market today are used to manage or cure diseases that previously had minimal or no effective treatment. However, the smaller patient populations for these drugs, coupled with the more complex manufacturing process inherent in producing most specialty drugs, result in a cost per prescription well in excess of the cost for a nonspecialty drug. The average retail prescriptions for generic and brand-name drugs cost $44 and $167, respectively2; by contrast, we see the average specialty prescription now costing more than $2200. The inherent high cost per specialty drug prescription substantially changes how payers need to evaluate “the best” specialty pharmacy with which to partner to help control specialty drug spending. The best specialty partner is one that can provide a competitive unit-price discount, while also maintaining a “one patient at a time” perspective, considering that each prescription dispensed that is not properly used by the patient represents a significant waste of healthcare dollars.

Clinical Programs: Maximize Clinical Outcomes The first responsibility of a specialty pharmacy should always be to ensure that patients who are prescribed a specialty therapy receive the maximum clinical benefit of that therapy. Although specialty drugs may cost a payer from $20,000 to more than $200,000 annually per person, a patient who is consistently adherent to therapy will gain the maximum benefit from the therapy, ultimately decreasing the downstream medical costs associated with the disease progression. Therefore, it is very important that when selecting a specialty pharmacy, payers understand how rigorously that organization works to keep patients adherent to their therapy. A specialty pharmacy must be dedicated to investing in and developing rigorous and structured patient-facing clinical programs, as well as developing an internal culture of clinical excellence through the use of specially trained technicians, nurses, and pharmacists. Reviewing a specialty pharmacy’s reporting package can prove helpful in evaluating the organization’s commitment to maximizing clinical outcomes.

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Case Example: Why the Lowest Unit Cost May Not Provide the Lowest Net Cost Let us consider a very simple utilization management program to illustrate how focusing exclusively on “unit cost” when choosing a specialty pharmacy vendor can backfire. Consider bids from 2 competing specialty pharmacies for the drug telaprevir (Incivek), a hepatitis C virus (HCV) infection therapy used in conjunction with ribavirin and peginterferon. Telaprevir has a well-documented treatment algorithm (response-guided therapy) that dictates that therapy should generally not exceed 12 weeks.5 The price for telaprevir from pharmacy A is AWP –16%, whereas pharmacy B offers a slightly more deeply discounted price of AWP –16.5%. With a monthly AWP for telaprevir of approximately $21,000,3 the resulting additional discount from pharmacy B is $105 per prescription, or $315 for a 12-week course of therapy. However, pharmacy B does not have a utilization management program for telaprevir, whereas pharmacy A does. At Walgreens, we continue to see physicians prescribing telaprevir for more than 12 weeks of therapy. Our clinical program intervenes with prescribers before dispensing any telaprevir prescription beyond the 12 weeks of typical therapy. (Of note, sometimes the extended length of therapy is simply the result of a prescriber writing a prescription for telaprevir and indicating that the prescription has “3 refills,” which translates to 16 weeks of therapy, not 12.) Assume a patient receives a telaprevir prescription for 16 weeks of therapy. Pharmacy A has a utilization management program in place that monitors the length of telaprevir therapy and intervenes with the prescriber when it is appropriate to stop therapy. Although pharmacy B may appear less expensive upon initial consideration, because of the lower unit cost, consider the impact to the payer’s overall cost of therapy as a result of pharmacy B’s lack of a utilization management program. Unless they are directed otherwise, most patients would attempt to fill the fourth month of telaprevir therapy, because they would see on their prescription label the number of refills remaining and would order a refill when the number of tablets is low. The end result is that the expected $315 of savings by utilizing the lowest unit-cost provider has backfired, and the pharmacy cost to treat the patient with telaprevir would become $70,140 for 16 weeks of therapy versus $52,920 had pharmacy A been servicing the patient. Pharmacy A’s utilization management program would have prevented the fourth month of therapy from being dispensed, which would have saved $17,220.

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Cost Management through Care Management

Utilization Management Programs: Minimize the Cost to Treat The second responsibility of a specialty pharmacy should be to work on behalf of the payer to minimize the “cost to treat” each patient. A thorough understanding of manufacturer programs, the clinical literature, and the standard of care within each disease state is essential. A specialty pharmacy should have active utilization management programs that intervene with the prescriber if a clinically equivalent but more cost-effective treatment is available for a patient. These programs augment a payer’s existing prior authorization and formulary strategies. A specialty pharmacy should have a variety of utilization management strategies in place, including doselevel monitoring, dose-frequency monitoring, formulary compliance programs, and waste minimization programs. For example, the drug ustekinumab (Stelara) is commercially available in a 45-mg and a 90-mg dose. The AWP of the 45-mg dose is approximately $27,000 annually, and the AWP of the 90-mg dose is approximately $54,000 annually.3 According to data documented in the US Food and Drug Administration (FDA)approved labeling, the 90-mg dose provides limited clinical efficacy improvement compared with the 45-mg dose for new patients weighing <220 pounds.4 As such, a specialty pharmacy that develops programs that increase the dispensing rate of the 45-mg dose in the population of patients weighing <220 pounds can dramatically impact the payer’s cost to manage patients who are using ustekinumab. A payer should understand all the utilization management programs and the accompanying reporting provided by the specialty pharmacy when selecting the best partner. This is especially important in oncology. As the number of FDA-approved oral cancer drugs continues to climb, and their labels expand to include additional indications, it is critical that the specialty pharmacy have a program in place to manage the side effects and waste associated with this expensive class of drugs. The Importance of Unit-Price Competitiveness The contractual discount that a specialty pharmacy offers a payer still plays a very prominent role in lowering a payer’s specialty pharmacy spending. However, this is not a factor that should be used on its own to determine which pharmacy can deliver the lowest specialty pharmacy cost. Pricing pressure on specialty pharmacies is intense, and the margins within the specialty pharmacy industry have compressed to a point that teeters on unsustainability. Payers feel pressure from their customers to

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lower costs and continue to look aggressively for the most cost-effective provider. To accomplish this, a few payers unilaterally choose to work with specialty pharmacies that offer the lowest unit cost per drug, but as demonstrated in the case example, that strategy could introduce unintended and insidious consequences. A few basis points (ie, a unit of measure used to describe the percentage change in the value or rate of a financial instrument; 1 basis point is equivalent to 0.01%) of unit-cost improvement will be quickly eroded if a pharmacy does not have clinical and utilization management programs in place to ensure that every prescription is dispensed in a clinically and economically appropriate fashion.

A specialty pharmacy must be dedicated to investing in and developing rigorous and structured patient-facing clinical programs. Specialty Pharmacy Contracting Models The specialty marketplace is dominated by 3 companies—Express Scripts Inc/Medco, CVS/Caremark, and Walgreens. These 3 companies comprise two thirds of the revenues driven by specialty pharmaceuticals.1 Consolidation continues in the marketplace, and many payers, such as Humana and Cigna, are providing specialty pharmacy distribution through company-owned pharmacies. Health plans and employer groups use various models to contract with specialty pharmacies. These models include exclusive (1 specialty pharmacy provider), narrow or limited network (2 or 3 providers), open access network, and disease-specific contracting with various vendors. Exclusive Model Some payers choose to work with 1 specialty pharmacy provider. The advantages of the exclusive model are better pricing, better control of the process, a more streamlined approach, better communication, and ease of use for physician networks. Another advantage would be aggregation of data, allowing for ease of implementation of clinical programs and possible savings guarantees. The disadvantages include a lack of competition and a lack of an immediately available backup vendor when the exclusive vendor suddenly cannot provide services. Narrow Network Some payers choose to work with 2 or 3 specialty pharmacy vendors in a narrow network. The advantages

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INDUSTRY TRENDS

of this model include vendor competition (because the vendors must compete for business), choice of specialty pharmacy providers, expanded access to limited-distribution drugs, and deeper pricing discounts than in an open network. Vendors with otherwise average customer service may work harder to pull through business, resulting in higher-quality service. The disadvantages include network confusion, data segregation, dealing with different operational processes, and the day-to-day issues in dealing with multiple vendors.

Open Network Some payers use an open network for specialty pharmacy providers. The advantages include a broad choice of vendors, the inclusion of local businesses and hospital partners, and ease of use for patients. The disadvantages include the poorest pricing, confusion, differing levels of quality, lack of control, and fragmented data reporting.

A specialty pharmacy that offers the lowest cost per unit is not necessarily the lowest-cost provider. Disease-Specific Contracting Some payers prefer to contract according to disease state. For example, a payer could use one vendor for multiple sclerosis drugs and another vendor for growth hormone. The theory is that vendors who demonstrate superior outcomes for specific disease states win the business. This could be called the “best practices” model. The advantages include benefiting from the highestquality and most cost-effective models available. The disadvantages include cumbersome contracting, confusion among prescribers about which specialty vendor to use, and nonoptimal pricing. Selecting a Model Legislative factors, network considerations, and contracting philosophy all influence a payer’s selection of a given contract model. However, if payers want to max-

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imize cost-savings and clinical outcomes, the exclusive model is usually selected, as a result of the following reasons: 1. Best pricing 2. Consistent data capture and reporting 3. A natural spirit of partnership between the specialty pharmacy and the payer 4. Greater utilization and intervention reporting 5. Consistent utilization management and clinical programs. Often, guarantees can be developed for specific programs, such as oral oncology split-fill programs or HCV infection programs, where interventions are made with providers on proper dosing of protease inhibitors. An exclusive vendor is able to demonstrate that the interventions made are resulting in consistent and measurable savings. Payers can then negotiate savings guarantees.

Conclusion A specialty pharmacy that offers the lowest cost per unit is not necessarily the lowest-cost provider. By using an exclusive specialty pharmacy provider, a payer can maximize unit-cost discounts and implement programs that drive savings far beyond what can be realized with the unit-cost discounts alone. Choosing the right specialty pharmacy partner can improve patients’ clinical outcomes, decrease downstream medical costs for the healthcare system, and minimize the cost to treat patients through intelligent prescriber interventions that are driven by rigorous utilization management programs. ■ Author Disclosure Statement Mr Einodshofer is an employee and stockholder of Walgreens. Mr Kansler is an employee of Walgreens.

References 1. EMD Serono. EMD Serono Specialty Digest. 8th ed. 2012. Rockland, MA. www.amcp. org/WorkArea/DownloadAsset.aspx?id=15229. Accessed August 2, 2012. 2. National Association of Chain Drug Stores. 2011-2012 Chain Pharmacy Industry Profile. 2012. Page 54. www.nacds.org/wmspage.cfm?parm1=6264. Accessed July 30, 2012. 3. Wolters Kluwer Health. Medi-Span. Price Rx. www.medispan.com/drug-pricinganalysis-pricerx.aspx. Accessed July 30, 2012. 4. Stelara (ustekinumab) prescribing information. Horsham, PA: Janssen Biotech Inc; 2012. 5. Incivek (telaprevir) prescribing information. Cambridge, MA: Vertex Pharmaceuticals Incorporated; 2012.

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Tell your patients about NovoTwist®, the first and only single-twist needle attachment on the market.

GOOD DESIGN

The benefits of NovoTwist® are:

Winner of the US Good Design™ award1

• Less time consuming for patients to attach • Features an audible and tactile confirmatory click for correct attachment • Available in 30G (8mm) and 32G Tip (5mm) needles Available for use with FlexPen® and other compatible Novo Nordisk devices.*

For more information, visit myflexpen.com or call 1-800-727-6500

* Designed to be used with Levemir® FlexPen®, NovoLog® FlexPen®, NovoLog® Mix 70/30 FlexPen®, and other compatible Novo Nordisk delivery devices. Please refer to the delivery device user manual to see if NovoTwist® can be used with your device. Also refer to the user manual for information on assembly and injection. Needles are sold separately and may require a prescription in some states. Reference: 1. http://www.chi-athenaeum.org/gdesign/2010/medical/index.html

FlexPen®, Levemir®, NovoLog®, and NovoTwist® are registered trademarks of Novo Nordisk A/S. © 2011 Novo Nordisk

Printed in the U.S.A.

0311-00002127-1

April 2011


CALL FOR PAPERS American Health & Drug Benefits offers an open forum for all healthcare participants to exchange ideas and present their data, innovations, and initiatives to facilitate patient-centered healthcare and benefit design models that meet the needs of all stakeholders—Distributors, Employers, Manufacturers, Patients, Payers, Providers, Purchasers, Regulators, and Researchers. Readers are invited to submit articles that aim at improving the quality of patient care and patient well-being while reducing or controlling costs, enhancing the health of communities and patient populations, as well as other topics relevant to benefit design with specific implications to policymakers, payers, and employers.

Areas of High Interest: • Health Economics Research • Health Plan Initiatives • Health Information Technology • Industry Trends • Innovations in Healthcare • Literature Reviews • Medicare/Medicaid • Patient Advocacy/Patient Care

• Adherence Concerns • Benefit Design • Case Studies • Comorbidities and Cost Issues • Comparative Effectiveness Research • Cost Analyses • Decision-Making Tools • Ethics in Medicine

• Pharmacoeconomics • Policy Issues • Prevention Initiatives • Reimbursement Strategies • Social Media and Health • Survey Results • Value-Based Healthcare • Wellness Programs

Clinical Topics of High Interest: AGING/DEMENTIA—With the aging of the US population there is a growing need for early implementation of outcomesbased preventive and therapeutic strategies for older people. ALLERGIES—Allergies, such as allergic or seasonal rhinitis, affect millions of Americans daily, resulting in a significant economic burden and human cost. Undertreatment and lack of adherence are common obstacles to patient management. ARTHRITIS—Musculoskeletal conditions are on the increase, yet many patients are undiagnosed and untreated. Comparing new and emerging therapies is a key target for improving patient outcomes and reducing costs. CANCER CARE—The growing focus on biologic agents dictates an enhanced study of these therapeutic options, including reimbursement policies and cost management. CARDIOVASCULAR DISEASE—Original, outcomesbased research on appropriate therapies, cost comparisons, emerging prevention strategies, and comparative effectiveness of best practices will enhance readers’ decision-making.

DIABETES, OBESITY—The increasing comorbid epidemics of these twin conditions mandates a thorough examination of best therapies, adherence issues, access, and prevention strategies. We invite articles that will address how to improve patient outcomes and best patient care. GASTROINTESTINAL CONDITIONS—Recognizing GI conditions, such as hepatitis C, Crohn’s disease, or inflammatory bowel disorder, remains a challenge. INFECTIOUS DISEASES—The spread of common and emerging pathogens within the hospital and in the community remains a major concern requiring increased vigilance. MENTAL DISORDERS—Depression, bipolar disorder, and schizophrenia exert a huge financial and human burden on individuals, employers, and payers. Topics of interest include comparative effectiveness analyses, best practices, and reimbursement.

PAIN MANAGEMENT—Chronic pain is associated with a slew of complicated medical disorders and an enormous economic burden, yet pain medications are still underused.

Manuscripts should follow the Manuscript Instructions for Authors (available at www.AHDBonline.com). Submit articles to editorial@engagehc.com. For more information, call 732-992-1892.

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For your patients with type 2 diabetes who need more than A1C control, choose Levemir ® (insulin detemir [rDNA origin] injection)

24/7 GLUCOSE CONTROL MORE

Karen’s doctor said taking Levemir ® (insulin detemir [rDNA origin] injection) once-daily may get her the control she needs & more Low rates of hypoglycemia In 1 study, approximately 45% of patients in each treatment arm achieved A1C <7% with no hypoglycemic events within the last 4 weeks of observation.1 t A single major hypoglycemic event was reported in the 70-90 mg/dL group; no major hypoglycemic events in the 80-110 mg/dL group t Minor hypoglycemia rates were 5.09 (70-90 mg/dL) and 3.16 (80-110 mg/dL) per patient-year*

From a 20-week, randomized, controlled, multicenter, open-label, parallel-group, treat-to-target trial using a self-titration algorithm in insulin-naïve patients with type 2 diabetes, A1C ≥7% and ≤9% on OAD therapy randomized to Levemir® and OAD (1:1) to 2 different fasting plasma glucose (FPG) titration targets (70-90 mg/dL [n=121] or 80-110 mg/dL [n=122]). At study end, in the 80-110 mg/dL group, 55% of patients achieved goal (A1C <7%) with A1C decrease of 0.9%. The mean A1C was 7%.1

Covered on more than 90% of managed care plans2† hypoglycemia usually reflects the time action profile of the administered insulin formulations. Glucose monitoring is essential for all patients receiving insulin therapy. Any changes to an insulin regimen should be made cautiously and only under medical supervision. Needles and Levemir ® FlexPen® must not be shared. Severe, life-threatening, generalized allergy, including anaphylaxis, can occur with insulin products, including Levemir ®. Adverse reactions associated with Levemir ® include hypoglycemia, allergic reactions, injection site reactions, lipodystrophy, rash and pruritus. Careful glucose monitoring and dose adjustments of insulin, including Levemir ®, may be necessary in patients with renal or hepatic impairment. Levemir ® has not been studied in children with type 2 diabetes, and in children with type 1 diabetes under the age of six.

Indications and Usage Levemir ® (insulin detemir [rDNA origin] injection) is indicated to improve glycemic control in adults and children with diabetes mellitus. Important Limitations of Use: Levemir ®isnotrecommendedforthetreatmentof diabetic ketoacidosis. Intravenous rapid-acting or short-acting insulin is the preferred treatment for this condition.

Important Safety Information Levemir ® is contraindicated in patients hypersensitive to insulin detemir or one of its excipients. Do not dilute or mix Levemir® with any other insulin solution, or use in insulin infusion pumps. Do not administer Levemir® intravenously or intramuscularly because severe hypoglycemia can occur. Hypoglycemia is the most common adverse reaction of insulin therapy, including Levemir®. The timing of

Please see brief summary of Prescribing Information on adjacent page. Needles are sold separately and may require a prescription in some states. *Minor=SMPG <56 mg/dL and not requiring third-party assistance.

On your iPhone®

Scan the QR code to download the NovoDose™ app to know how to optimally dose Levemir®

Intended as a guide. Lower acquisition costs alone do not necessarily reflect a cost advantage in the outcome of the condition treated because other variables affect relative costs. Formulary status is subject to change.

References: 1. Blonde L, Merilainen M, Karwe V, Raskin P; TITRATE™ Study Group. Patient-directed titration for achieving glycaemic goals using a once-daily basal insulin analogue: an assessment of two different fasting plasma glucose targets - the TITRATE™ study. Diabetes Obes Metab. 2009;11(6):623-631. 2. Data on file. Novo Nordisk Inc, Princeton, NJ. iPhone ® is a registered trademark of Apple, Inc. FlexPen® and Levemir ® are registered trademarks and NovoDose™ is a trademark of Novo Nordisk A/S. © 2012 Novo Nordisk Printed in the U.S.A. 0911-00005042-1 April 2012


LEVEMIR® (insulin detemir [rDNA origin] injection) Rx ONLY BRIEF SUMMARY. Please consult package insert for full prescribing information. INDICATIONS AND USAGE: LEVEMIR® is indicated to improve glycemic control in adults and children with diabetes mellitus. Important Limitations of Use: LEVEMIR® is not recommended for the treatment of diabetic ketoacidosis. Intravenous rapid-acting or short-acting insulin is the preferred treatment for this condition. CONTRAINDICATIONS: LEVEMIR® is contraindicated in patients with hypersensitivity to LEVEMIR® or any of its excipients. Reactions have included anaphylaxis. WARNINGS AND PRECAUTIONS: Dosage adjustment and monitoring: Glucose monitoring is essential for all patients receiving insulin therapy. Changes to an insulin regimen should be made cautiously and only under medical supervision. Changes in insulin strength, manufacturer, type, or method of administration may result in the need for a change in the insulin dose or an adjustment of concomitant anti-diabetic treatment. As with all insulin preparations, the time course of action for LEVEMIR® may vary in different individuals or at different times in the same individual and is dependent on many conditions, including the local blood supply, local temperature, and physical activity. Administration: LEVEMIR® should only be administered subcutaneously. Do not administer LEVEMIR® intravenously or intramuscularly. The intended duration of activity of LEVEMIR® is dependent on injection into subcutaneous tissue. Intravenous or intramuscular administration of the usual subcutaneous dose could result in severe hypoglycemia. Do not use LEVEMIR® in insulin infusion pumps. Do not dilute or mix LEVEMIR® with any other insulin or solution. If LEVEMIR® is diluted or mixed, the pharmacokinetic or pharmacodynamic profile (e.g., onset of action, time to peak effect) of LEVEMIR® and the mixed insulin may be altered in an unpredictable manner. Hypoglycemia: Hypoglycemia is the most common adverse reaction of insulin therapy, including LEVEMIR®. The risk of hypoglycemia increases with intensive glycemic control. Patients must be educated to recognize and manage hypoglycemia. Severe hypoglycemia can lead to unconsciousness or convulsions and may result in temporary or permanent impairment of brain function or death. Severe hypoglycemia requiring the assistance of another person or parenteral glucose infusion, or glucagon administration has been observed in clinical trials with insulin, including trials with LEVEMIR®. The timing of hypoglycemia usually reflects the time-action profile of the administered insulin formulations. Other factors such as changes in food intake (e.g., amount of food or timing of meals), exercise, and concomitant medications may also alter the risk of hypoglycemia. The prolonged effect of subcutaneous LEVEMIR® may delay recovery from hypoglycemia. As with all insulins, use caution in patients with hypoglycemia unawareness and in patients who may be predisposed to hypoglycemia (e.g., the pediatric population and patients who fast or have erratic food intake). The patient’s ability to concentrate and react may be impaired as a result of hypoglycemia. This may present a risk in situations where these abilities are especially important, such as driving or operating other machinery. Early warning symptoms of hypoglycemia may be different or less pronounced under certain conditions, such as longstanding diabetes, diabetic neuropathy, use of medications such as beta-blockers, or intensified glycemic control. These situations may result in severe hypoglycemia (and, possibly, loss of consciousness) prior to the patient’s awareness of hypoglycemia. Hypersensitivity and allergic reactions: Severe, life-threatening, generalized allergy, including anaphylaxis, can occur with insulin products, including LEVEMIR®. Renal Impairment: No difference was observed in the pharmacokinetics of insulin detemir between non-diabetic individuals with renal impairment and healthy volunteers. However, some studies with human insulin have shown increased circulating insulin concentrations in patients with renal impairment. Careful glucose monitoring and dose adjustments of insulin, including LEVEMIR®, may be necessary in patients with renal impairment. Hepatic Impairment: Nondiabetic individuals with severe hepatic impairment had lower systemic exposures to insulin detemir compared to healthy volunteers. However, some studies with human insulin have shown increased circulating insulin concentrations in patients with liver impairment. Careful glucose monitoring and dose adjustments of insulin, including LEVEMIR®, may be necessary in patients with hepatic impairment. Drug interactions: Some medications may alter insulin requirements and subsequently increase the risk for hypoglycemia or hyperglycemia. ADVERSE REACTIONS: The following adverse reactions are discussed elsewhere: Hypoglycemia; Hypersensitivity and allergic reactions. Clinical trial experience: Because clinical trials are conducted under widely varying designs, the adverse reaction rates reported in one clinical trial may not be easily compared to those rates reported in another clinical trial, and may not reflect the rates actually observed in clinical practice. The frequencies of adverse reactions (excluding hypoglycemia) reported during LEVEMIR® clinical trials in patients with type 1 diabetes mellitus and

type 2 diabetes mellitus are listed in Tables 1-4 below. See Tables 5 and 6 for the hypoglycemia findings. Table 1: Adverse reactions (excluding hypoglycemia) in two pooled clinical trials of 16 weeks and 24 weeks duration in adults with type 1 diabetes (adverse reactions with incidence ≥ 5%)

Upper respiratory tract infection Headache Pharyngitis Influenza-like illness Abdominal Pain

LEVEMIR®, % (n = 767) 26.1 22.6 9.5 7.8 6.0

NPH, % (n = 388) 21.4 22.7 8.0 7.0 2.6

Table 2: Adverse reactions (excluding hypoglycemia) in a 26-week trial comparing insulin aspart + LEVEMIR® to insulin aspart + insulin glargine in adults with type 1 diabetes (adverse reactions with incidence ≥ 5%)

Upper respiratory tract infection Headache Back pain Influenza-like illness Gastroenteritis Bronchitis

LEVEMIR®, % (n = 161) 26.7 14.3 8.1 6.2 5.6 5.0

Glargine, % (n = 159) 32.1 19.5 6.3 8.2 4.4 1.9

Table 3: Adverse reactions (excluding hypoglycemia) in two pooled clinical trials of 22 weeks and 24 weeks duration in adults with type 2 diabetes (adverse reactions with incidence ≥ 5%)

Upper respiratory tract infection Headache

LEVEMIR®, % (n = 432) 12.5 6.5

NPH, % (n = 437) 11.2 5.3

Table 4: Adverse reactions (excluding hypoglycemia) in a 26-week clinical trial of children and adolescents with type 1 diabetes (adverse reactions with incidence ≥ 5%)

Upper respiratory tract infection Headache Pharyngitis Gastroenteritis Influenza-like illness Abdominal pain Pyrexia Cough Viral infection Nausea Rhinitis Vomiting

LEVEMIR®, % (n = 232) 35.8 31.0 17.2 16.8 13.8 13.4 10.3 8.2 7.3 6.5 6.5 6.5

NPH, % (n = 115) 42.6 32.2 20.9 11.3 20.9 13.0 6.1 4.3 7.8 7.0 3.5 10.4

Hypoglycemia: Hypoglycemia is the most commonly observed adverse reaction in patients using insulin, including LEVEMIR®. Tables 5 and 6 summarize the incidence of severe and non-severe hypoglycemia in the LEVEMIR® clinical trials. Severe hypoglycemia was defined as an event with symptoms consistent with hypoglycemia requiring assistance of another person and associated with either a blood glucose below 50 mg/ dL or prompt recovery after oral carbohydrate, intravenous glucose or glucagon administration. Non-severe hypoglycemia was defined as an asymptomatic or symptomatic plasma glucose < 56 mg/dL (<50 mg/dL in Study A and C) that was self-treated by the patient. The rates of hypoglycemia in the LEVEMIR® clinical trials (see Section 14 for a description of the study designs) were comparable between LEVEMIR®-treated patients and non-LEVEMIR®-treated patients (see Tables 5 and 6).


Table 5: Hypoglycemia in Patients with Type 1 Diabetes Study A Type 1 Diabetes Adults 16 weeks In combination with insulin aspart Twice-Daily Twice-Daily NPH LEVEMIR® Severe hypo- Percent of patients 10.6 8.7 glycemia with at least 1 event (14/132) (24/276) (n/total N) Event/patient/year 0.52 0.43 89.4 88.0 Non-severe Percent of patients (118/132) (243/276) hypoglycemia (n/total N) Event/patient/year 26.4 37.5

Study B Type 1 Diabetes Adults 26 weeks In combination with insulin aspart Twice-Daily Once-Daily LEVEMIR® Glargine

Study C Type 1 Diabetes Adults 24 weeks In combination with regular insulin Once-Daily Once-Daily NPH LEVEMIR®

Study D Type 1 Diabetes Pediatrics 26 weeks In combination with insulin aspart Once- or Twice Once- or Twice Daily LEVEMIR® Daily NPH

5.0 (8/161)

10.1 (16/159)

7.5 (37/491)

10.2 (26/256)

15.9 (37/232)

20.0 (23/115)

0.13 82.0 (132/161) 20.2

0.31 77.4 (123/159) 21.8

0.35 88.4 (434/491) 31.1

0.32 87.9 (225/256) 33.4

0.91 93.1 (216/232) 31.6

0.99 95.7 (110/115) 37.0

Table 6: Hypoglycemia in Patients with Type 2 Diabetes

Severe hypo- Percent of patients with at least 1 event glycemia (n/total N) Event/patient/year Non-severe Percent of patients hypoglycemia (n/total N) Event/patient/year

Study E Type 2 Diabetes Adults 24 weeks In combination with oral agents Twice-Daily NPH Twice-Daily LEVEMIR® 0.4 2.5 (1/237) (6/238) 0.01 0.08 40.5 64.3 (96/237) (153/238) 3.5 6.9

Insulin Initiation and Intensification of Glucose Control: Intensification or rapid improvement in glucose control has been associated with a transitory, reversible ophthalmologic refraction disorder, worsening of diabetic retinopathy, and acute painful peripheral neuropathy. However, long-term glycemic control decreases the risk of diabetic retinopathy and neuropathy. Lipodystrophy: Long-term use of insulin, including LEVEMIR®, can cause lipodystrophy at the site of repeated insulin injections. Lipodystrophy includes lipohypertrophy (thickening of adipose tissue) and lipoatrophy (thinning of adipose tissue), and may affect insulin adsorption. Rotate insulin injection sites within the same region to reduce the risk of lipodystrophy. Weight Gain: Weight gain can occur with insulin therapy, including LEVEMIR®, and has been attributed to the anabolic effects of insulin and the decrease in glucosuria. Peripheral Edema: Insulin, including LEVEMIR®, may cause sodium retention and edema, particularly if previously poor metabolic control is improved by intensified insulin therapy. Allergic Reactions: Local Allergy: As with any insulin therapy, patients taking LEVEMIR® may experience injection site reactions, including localized erythema, pain, pruritis, urticaria, edema, and inflammation. In clinical studies in adults, three patients treated with LEVEMIR® reported injection site pain (0.25%) compared to one patient treated with NPH insulin (0.12%). The reports of pain at the injection site did not result in discontinuation of therapy. Rotation of the injection site within a given area from one injection to the next may help to reduce or prevent these reactions. In some instances, these reactions may be related to factors other than insulin, such as irritants in a skin cleansing agent or poor injection technique. Most minor reactions to insulin usually resolve in a few days to a few weeks. Systemic Allergy: Severe, life-threatening, generalized allergy, including anaphylaxis, generalized skin reactions, angioedema, bronchospasm, hypotension, and shock may occur with any insulin, including LEVEMIR®, and may be life-threatening. Antibody Production: All insulin products can elicit the formation of insulin antibodies. These insulin antibodies may increase or decrease the efficacy of insulin and may require adjustment of the insulin dose. In phase 3 clinical trials of LEVEMIR®, antibody development has been observed with no apparent impact on glycemic control. Postmarketing experience: The following adverse reactions have been identified during post approval use of LEVEMIR®. Because these reactions are reported voluntarily from a population of uncertain size, it is not always possible to reliably estimate their frequency or establish a causal relationship to drug exposure. Medication errors have been reported during post-approval use of LEVEMIR® in which other insulins, particularly rapid-acting or short-acting insulins, have been accidentally administered instead of LEVEMIR®. To avoid medication errors between LEVEMIR® and other insulins, patients should be instructed always to verify the insulin label before each injection.

Study F Type 2 Diabetes Adults 22 weeks In combination with insulin aspart Once- or Twice Daily NPH Once- or Twice Daily LEVEMIR® 1.5 4.0 (3/195) (8/199) 0.04 0.13 32.3 32.2 (63/195) (64/199) 1.6 2.0

More detailed information is available upon request.

For information about LEVEMIR® contact: Novo Nordisk Inc., 100 College Road West Princeton, NJ 08540 1-800-727-6500 www.novonordisk-us.com Manufactured by: Novo Nordisk A/S DK-2880 Bagsvaerd, Denmark Revised: 1/2012 Novo Nordisk®, Levemir®, NovoLog®, FlexPen®, and NovoFine® are registered trademarks of Novo Nordisk A/S. LEVEMIR® is covered by US Patent Nos. 5,750,497, 5,866,538, 6,011,007, 6,869,930 and other patents pending. FlexPen® is covered by US Patent Nos. 6,582,404, 6,004,297, 6,235,400 and other patents pending. © 2005-2012 Novo Nordisk 0212-00007333-1 2/2012


CLINICAL

Review ARticle

Conceptual and Analytical Considerations toward the Use of Patient-Reported Outcomes in Personalized Medicine Demissie Alemayehu, PhD; Joseph c. cappelleri, PhD, MPH

Stakeholder Perspective, page 316

Am Health Drug Benefits. 2012;5(5):310-317 www.AHDBonline.com Disclosures are at end of text

Background: Patient-reported outcomes (PROs) can play an important role in personalized medicine. PROs can be viewed as an important fundamental tool to measure the extent of disease and the effect of treatment at the individual level, because they reflect the self-reported health state of the patient directly. However, their effective integration in personalized medicine requires addressing certain conceptual and methodological challenges, including instrument development and analytical issues. Objectives: To evaluate methodological issues, such as multiple comparisons, missing data, and modeling approaches, associated with the analysis of data related to PRO and personalized medicine to further our understanding on the role of PRO data in personalized medicine. Discussion: There is a growing recognition of the role of PROs in medical research, but their potential use in customizing healthcare is not widely appreciated. Emerging insights into the genetic basis of PROs could potentially lead to new pathways that may improve patient care. Knowledge of the biologic pathways through which the various genetic predispositions propel people toward negative or away from positive health experiences may ultimately transform healthcare. Understanding and addressing the conceptual and methodological issues in PROs and personalized medicine are expected to enhance the emerging area of personalized medicine and to improve patient care. This article addresses relevant concerns that need to be considered for effective integration of PROs in personalized medicine, with particular reference to conceptual and analytical issues that routinely arise with personalized medicine and PRO data. Some of these issues, including multiplicity problems, handling of missing valuesand modeling approaches, are common to both areas. It is hoped that this article will help to stimulate further research to advance our understanding of the role of PRO data in personalized medicine. Conclusion: A robust conceptual framework to incorporate PROs into personalized medicine can provide fertile opportunity to bring these two areas even closer and to enhance the way a specific treatment is attuned and delivered to address patient care and patient needs.

P

ersonalized medicine aims to assist healthcare providers to individualize a patient treatment based on the patient’s attributes, which may include biomarkers, genetics, demographic characteristics, and other covariates. Much progress has been made in recent years in the translational research areas of genomics, proteomics, and metabolomics, and several biomarkers have been identified for a number of important diseases, including atherosclerosis, cancer, and rheumatoid arthritis. Many of these biomarkers are now being studied in clinical trials to identify subgroups of

Dr Alemayehu is Vice President, Specialty Care Biostatistics, Pfizer Inc, New York, NY, and Dr Cappelleri is Senior Director, Specialty Care Biostatistics, Pfizer Inc, Groton, CT.

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patients who best benefit from a given therapy. However, despite the growing importance of patient-reported outcomes (PROs) in medical research, their role in customizing healthcare is not widely recognized. Information solicited directly from patients about their health status or health-related quality of life (QOL), disease burden, or other aspects of their disease or treatment should be an essential component of any treatment paradigm that relies on genetic and other patient-specific information to ensure optimal care delivery for the individual patient. Broadly defined, a PRO is any report on the status of a patient’s clinical condition that comes directly from the patient, without interpretation of the patient’s response by a clinician or by anyone else. “Patient-

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reported outcomes” is an umbrella term that includes a variety of subjective outcomes, such as pain, fatigue, depression, aspects of well-being (eg, physical, functional, psychological), treatment satisfaction, health-related QOL, and physical symptoms, such as nausea and vomiting. PROs are often relevant for studying different conditions—such as pain, erectile dysfunction, fatigue, migraine, anxiety, and depression—that cannot be assessed adequately without input from the patient on the impact of the disease or the treatment. To be useful to patients and to other decision makers (eg, physicians, regulatory agencies, reimbursement authorities) who are stakeholders in medical care, a PRO must undergo a validation process to confirm that it is reliably measuring what it is intended to measure. The focus of this article is on the analysis and reporting of PRO data derived from standardized PRO instruments for use mainly in clinical research, such as in clinical trials and in drug development. In recent years, there has been growing evidence for the impact of genetics on QOL and on PROs.1-7 Most notably, Raat and colleagues describe the value of a population-based prospective cohort study from fetal life and beyond in Rotterdam, the Netherlands, as a template that enables candidate gene study and genome-wide association study regarding the QOL of mothers and their young children.3 Although several articles refer to QOL when the focus is on groups of individuals, be they patients or not,1-3 overall considerations about QOL in the context of personalized medicine are equally applicable to the more general term “PRO” when referring to any health-related report coming directly from the patient. Rijsdijk and colleagues found that the overall heritability of psychosocial distress ranged from 20% to 44% in their study.4 In other studies, evidence of genetic influences has been reported for PROs.5,6 Although much research is still needed to determine the precise proportion of variability in PRO that is explained by genetic factors, considerable progress has been seen in some areas, such as in oncology, to quantify the association between polymorphisms and PROs.7 Personalized medicine involves the customization of healthcare tailored to the individual patient by use of genetic and other information, including PROs such as symptoms, functional status, treatment satisfaction, and health-related QOL. Yet methodological advancements needed for PROs and genetics are lacking. Insights into the genetics of PROs will ultimately allow early identification of patients susceptible to PRO deficits, as well as to target care in advance. Therefore, by unraveling the genetic understandings of PROs (eg, what specific single-nucleotide polymorphisms, on which specific genes, are associated with pain), researchers will have a greater

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KEY POINTS ➤

“Patient-reported outcomes” (PROs) refers to any report on the status of a patient’s clinical condition that comes directly from the patient, without interpretation by a clinician or by anyone else. Personalized medicine aims to individualize a patient treatment based on the patient’s unique attributes. By identifying patients who are susceptible to certain poor aspects of patient-reported health status (eg, pain), healthcare stakeholders will be in a better position to target preventive strategies or provide specific interventions. PROs must undergo a validation process to be useful to patients and stakeholders in medical care. A major step in the incorporation of PROs in personalized medicine is the establishment and use of standardized instruments that have proven reliability and validity. The most important challenge in personalized medicine is to establish a statistical framework for data analysis that links outcomes to concepts of interest, and subsequently links those to specific aspects of patient-reported health status. Incorporating PROs into personalized medicine can provide information to enhance patient care.

understanding of diagnosis and treatment management for an individual patient—an understanding that has the potential to lead to improved survival, PRO assessments, and health service delivery. Effective use of PRO data in the context of personalized medicine entails a careful evaluation of conceptual and methodological issues associated with PRO and with personalized medicine. Guidelines and best practices have been developed to strengthen the value of the data from those two fields.8-12 The issues surrounding PRO data, which are generally used to quantify PROs in a structured way, have been a particular focus of concerted research.8 Regulatory guidelines and other guidance documents have also been issued to address several central concerns.9,10 Emerging insights into the genetic basis of PROs could potentially lead to new pathways to help to improve patient care. Knowledge of the biologic pathways through which the various genetic predispositions propel people toward negative, or away from positive, health experiences may ultimately transform healthcare. By identifying patients who are susceptible to certain poor aspects of patient-reported health status (eg, pain), healthcare stakeholders will be in a better position to target preventive strategies or provide specific interven-

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tions, such as pharmacologic treatment, psychological counseling, lifestyle and behavioral changes, or a combination thereof. The risk of not making PROs an integral component in the genetic profile may have, by not imposing an effective targeted early intervention, a profound and untoward impact wherein individuals experience substantially diminished well-being. Under such a circumstance, healthcare providers would miss the opportunity to effectively screen patients to discover who would likely experience PRO deficits associated with a disease or its treatment or both. Consequently, treatment decision-making and patient care would be compromised. Furthermore, genetic research shares some of the often-encountered issues that arise in PRO studies, including multiplicity of end points, missing data, reliability, and validity.11 For genetic research, the need for methodological standards as a resource for researchers has been the focus of a recent study.12 The role of QOL in personalized medicine has also garnered increasing attention, in part as a result of the activities of organizations such as the GENEQOL Consortium, which aims to promote research on biologic mechanisms, potential genes, and genetic variants that may be involved in QOL.13 Advances in that area include summaries on the genetic background of common symptoms and overall well-being.13 In this article we consider the role of PRO data in personalized medicine, with a particular reference to analytical issues that routinely arise with personalized medicine and PRO data, including multiplicity problems, missing values, and statistical models. Given the abundance of material relating to personalized medicine, the focus of this article is on the relationship between PRO data analysis and reporting and personalized medicine. Other important aspects of PROs, including data collection and its storage for ease of use in the clinical setting, as well as integration of such data with clinical guidelines of care, are beyond the scope of this article.

Challenges in Personalized Medicine Clinical Trial Design The designs of studies relating to PROs and personalized medicines can affect the analysis of the data and the results of the trials. In both cases, the results may be impacted by biases emanating from flawed designs, particularly designs that do not enable collection of data on pertinent end points or those that do not ensure adequate balance across treatment groups with respect to relevant patient characteristics. In addition, the choice of analytical methods is often determined by the type of study design used to generate data. For example, if PRO or per-

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sonalized medicine data are collected over time, the analytical methods to be used would be different from those that collect data only at a specified time point. Randomized controlled trials (RCTs) are the gold standard for evaluating the comparative risks and benefits of alternative treatment options. However, RCTs are typically designed to address a relatively narrow set of hypotheses and often lack generalizability to realworld settings as a result of strict study protocol criteria about patient selection and follow-up. Accordingly, in the study of personalized medicine and PROs, RCTs may not provide reliable data to characterize the profile of a drug on those excluded subjects. An alternative approach that incorporates both randomization and generalizability is the so-called pragmatic RCTs. Such trials typically aim at reflecting the heterogeneity of patients in the real world, thereby facilitating the collection of pertinent data germane to personalized medicine, as well as to PRO research. Developments in personalized therapies have been affected by many experimental, modeling, and analytical challenges, including handling multiple end points and missing values. A key step in operationalizing personalized medicine is â&#x20AC;&#x153;stratified medicine,â&#x20AC;? wherein the goal is to use clinical biomarkers to identify subgroups of patients who are likely to benefit from a given therapy.14 In conventional clinical trial designs, stratified medicine is routinely executed using alternative covariate-adjusted designs to ensure balance of treatment assignment across various strata defined by patient-level attributes. However, existing approaches fall short of handling the complex covariate structure that typically arises in clinical trials related to personalized medicine.15 A related issue is the inability of common trial designs to efficiently detect the interaction between treatment and biomarkers. Because of ethical and cost considerations, the number of subjects recruited for such studies is seldom adequate to incorporate the desired amount of covariate information into the design, thereby lowering the efficiency, or the precision, of the estimated effects of treatments. The widely publicized methods of adaptive trial designs16 to reduce cost and enhance designs based on accumulating information are not yet fully developed for use in personalized medicine, which generally involves covariate information. From an analytical standpoint, among the major issues related to personalized medicine are multiplicity, that is, conducting multiple statistical inferences on potentially several outcomes, and missing data. Perhaps the single most important challenge in personalized medicine is the establishment of a robust statistical framework for multidimensional patient-level data analysis. The traditional

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approaches are no longer viable to address the cases where the number of study variables is substantially larger than the number of patients or the units of analysis.17 Furthermore, approaches developed for dealing with missing data in conventional trials need substantial modification to handle the situations that arise in personalized medicine, because the latter involve larger data points than those generated by typical PRO trials.18 The usual assumption of linearity that is basic to data analytical approaches for the conventional clinical trials may not be valid to model the complex relationships between genetic and nongenetic patient characteristics. In this regard, advances in the application of network graphs and other machine learning, and data-mining techniques in the analysis of high-dimensional data seem to be promising strategies.16 These advanced analytical techniques are particularly useful for mitigating the issues associated with subgroup and heterogeneity analyses.19 Despite the known pitfalls of such analyses, even in conventional randomized clinical trials,20 there is still a methodological gap in researching a reliable approach, especially for personalized medicine.

Issues Concerning PRO Data Analysis Instrument Development and Validation A major step in the incorporation of PROs into personalized medicine is the establishment and use of standardized instruments with proven reliability and validity. Although there are numerous validated instruments that measure different domains of health from the perspective of the patient, the choice of a PRO instrument is a function of the research question, the disease, and the population under study. A partial list of common PRO instruments can be found, for example, in a book by Fayers and Machin.21 The development of a new PRO instrument for a given disease requires the establishment of a robust and theory-based conceptual framework, linking the desired outcome to the concept of interest, and subsequently linking that concept to the specific symptoms or other aspects (such as physical functioning) being measured. The use of focus groups and cognitive interviews with patients can provide the considerable input needed to establish validity and to ensure that the PRO questionnaire covers what patients consider important. Related to but distinct from conceptual issues, analytical measurement using standard psychometric methods should be applied to test the reliability, validity, and responsiveness of the PRO measure. Among them, exploratory factor analysis and confirmatory factor analysis (as discussed below) should be considered to examine the factor structure regarding which items go with what domains; in addition, item response theory

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(also discussed below) should also be considered to further evaluate the performance of individual items and their response categories. Some of the analytical issues that arise in the context of personalized medicine data also arise in the context of PRO data analysis. These issues include longitudinal analysis, item response theory, and missing data. In addition, PRO data may require specialized approaches that facilitate interpretation of results. Although the analytical topics are not necessarily particular to personalized medicine, they do share common ground with it.

Longitudinal Analysis From a modeling perspective, longitudinal analysis appears to be well suited for PRO data. For outcomes measured over time, the data may be analyzed using several approaches, with the two most common or useful being random coefficient models (ie, time taken as continuous) and repeated measures models (ie, time taken as categorical). Other approaches, which may also be used for discrete outcomes, include generalized estimating equations and generalized linear mixed-effects models. Details on longitudinal analysis can be found elsewhere.22 An analytical framework for individual response using mixed-effects analyses has the ability to distinguish systematic or explained effects, which are true for all persons sharing a common set of covariate values (ie, fixed effects), not only from random error (ie, residual effects) but also from reliable individual differences, which are inferred and unexplained within the statistical model (ie, random effects). Mixed-effects modeling subsumes average treatment differences and individual differences in a unified statistical analysis. Adding a set of substantive predictors that can explain the attributes of individual initial status on a PRO and therapeutic changes on that PRO could be potent determinants of individual response. Results from mixed-effects models can be portrayed in graphic displays that summarize the spectrum of individual responses and associated prediction intervals, which can convey clinically meaningful information regarding the impact of a treatment on an individual’s PRO score.23 Subgroups are often undertaken to examine heterogeneity or differences in treatment effect among patients. Perhaps the treatment works better for one subgroup over another. Limitations of subgroup analyses— the conventional means for exploring differences in treatment effect based on patient characteristics—are well documented.19 Undisciplined searches for patient subgroups can result in “fishing expeditions,” leading to incorrect inferences and conclusions. Too many characteristics exist that can potentially influence treatment effect; myriad subgroup analyses can lead to underpow-

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ered results or be vulnerable to false-positive results related to multiple comparisons.20

Item Response Theory Item response theory is a statistical theory consisting of nonlinear logistic models to express the probability of a particular response to a scale item as a function of the quantitative attribute of interest (latent “unobservable” trait or concept, such as depression).24 The mathematical description for the item response is known as an “item characteristic curve,” which gives the probability of responding to a particular category of an item for an individual with an estimated amount on the attribute. Each item typically has its own level of difficulty (items that are more difficult are harder to endorse) and can have its own level of discrimination (items with more discrimination are more likely to distinguish among persons with varying levels on the attribute). The applications and relevance of item response theory for PROs has increased considerably over the past several years. For example, item response theory has been the cornerstone of the Patient-Reported Outcomes Measurement Information System (PROMIS), a large initiative of the National Institutes of Health (NIH), which aims to revolutionize the way PROs are selected and used in clinical research and practice.25 The broad objectives of the NIH PROMIS network are to develop and test a large bank of items measuring PROs; create a computerized adaptive testing system that allows for efficient, psychometrically robust assessment of PROs in clinical research involving a wide range of chronic diseases; and create a publicly available system that can be added to and modified periodically, and that allows clinical researchers to access a common repository of items and computerized adaptive tests at the individual patient level. Missing Data Methods to address missing data for clinical outcomes in clinical trials, including the PRO questionnaire with all items missing, have been published.26 In the context of PRO analysis, missing data may arise in a variety of ways. For example, data may be missing on a patient for certain visits because of poor compliance. Such data may be missing for an entire domain or for specific items within domains. Although the former is generally true for other clinical end points, the latter is more specifically associated with PRO measures. In all cases, the handling of the missing values is a function of the “missingness” mechanism. When it can be justified that the missing data are random, well-established approaches, such as mixedeffects modeling, can we successfully address the problem. By contrast, if the missingness is nonrandom, then the

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data analysis requires caution. Although there are techniques to determine if the missing data are random or nonrandom, no definitive way is available to rule out the latter. Therefore, in case of doubt, sensitivity analysis should be performed to ensure the robustness of the findings under alternate scenarios.18,22,26

Interpretation An inherent and fundamental issue for a PRO is its meaning. Interpretation of PRO scores, although distinct from validity and reliability, is central for a PRO to gain currency and usefulness. Approaches to interpretation of PRO scores are available.21,27,28 Methods generally fall under two broad strategies—anchored-based approaches and distribution-based approaches—and the variations within them are aimed at enhancing the understanding and meaning of PRO scores. An anchor is a measure or criterion related to the targeted PRO under examination, and it can be different from, or even part of, the PRO measure under consideration. The chosen anchor should be clearly understood in context and be easier to interpret than the PRO measure of interest, and it should be appreciably correlated with the targeted PRO. An anchor-based approach links the targeted concept of the PRO to the meaningful concept (or criterion) emanating from the anchor, such as patient assessment on the severity of the condition. Four avenues to apply an anchor-based methodology include percentages based on thresholds, criterion group interpretation, content-based interpretation, and clinically important difference.21,27,28 Distribution-based approaches exist for individual difference and group difference, and they can give valuable insights into the magnitude of an effect. It is well known that changes for an individual need to be much larger than changes for a group to be statistically significant. Several similar approaches to determine the statistical significance of individual change have been described, including standard error of measurement, standard error of prediction, and reliable change index.29 Three useful distribution-based methods for determining the importance of group differences include effect size, responder analysis, and cumulative proportions.21,28 Distribution methods for group differences allow for a standardization of different scales with various ranges and ways of scoring. A limitation of distribution-based methods in general is that they do not provide information about clinical meaningfulness, because they are strictly statistically based approaches. Toward a Conceptual Framework for PROs in Personalized Medicine As discussed by Sprangers and colleagues, the study of

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the genetic disposition of PROs requires a conceptual model to establish the relationships among QOL domains, biologic mechanisms, and genetic variants.1 A model that appears to be appropriate in this setting is the one introduced by Wilson and Cleary, which links biologic factors and patient-reported QOL.30 This model has been further enhanced by Spranger sand colleagues to include the genetic underpinnings of biologic variables, as well as other individual characteristics.1 Notably, the model is general enough to allow the study of interactions among patient characteristics and environment and genetic factors. Sprangers and colleagues focuse on QOL, because the research and the paradigm center mainly on the individual in general, whether or not that person’s response is patient-reported.1 These researchers reserve the more general term “PRO” in their article for situations applied to any selfreport of health coming directly from the patient.1 A framework has been proposed to assess risk-based heterogeneity of treatment effects, and this framework is especially promising in personalized medicine and PRO assessment.31,32 This framework, which acknowledges that “one size does not fit all” in addressing individual differences, has been originally applied to a binary outcome, be it a PRO or not. The framework, however, can be adapted to continuous PRO (and nonPRO) outcomes and consists of the five following recommendations31,32: • Evaluate and report on the distribution of baseline risk in the overall study population and in the separate treatment arms using a risk prediction tool • Report how relative and absolute changes vary by baseline, using a multivariate prediction tool, in the primary subgroup analyses • Prespecify additional primary subgroup analyses for single variables and limit these to patient attributes with strong pathophysiologic or empirical justification • Distinguish secondary (exploratory) subgroup analyses from primary subgroup comparisons • Report all conducted analyses with statistical testing of heterogeneity of treatment effects using appropriate methods (eg, interaction terms) and avoid overinterpretation. Multiplicity issues, which have been noted earlier in the context of genomic and subgroup analysis, are also important in the analysis of PRO data. First, multiple end points are an integral component of PRO analysis. In addition, there may be a desire to evaluate treatment effects at different time points and for various subgroups. Therefore, when used in the context of personalized medicine, the problem of missingness is compounded and poses further analytical challenges. Approaches that adjust for multiplicity exist, depend-

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ing on research objectives, end points, decision rules, and other factors.33 These approaches may include the use of familiar standard statistical techniques (eg, false discovery rates and step down, step up, and other gatekeeping procedures), as well as definitions of composite end points to reduce the number of potential end points to be evaluated. Composite end points, however, require caution and subject matter expertise to ensure that their interpretation, validity, and original intent are preserved. Of special interest in personalized medicine are the individual differences in treatment responses in longitudinal data.23,34 These differences describe how patients respond in various ways to the same treatment and qualify the generality of an overall treatment effect. Differences in treatment response are generally the result of personal dispositions (encoded in genes, bodies, or brains) that, along with clinical and demographic characteristics, enable patients to respond in certain ways to particular therapies. In this regard, the approaches discussed earlier in the context of PRO longitudinal data analysis may serve as a framework to incorporate genetic and other patient-level characteristics.

Conclusions With the growing interest in personalized medicine, there are compelling reasons to incorporate PROs as an integral part of the research endeavor in personalized medicine. Specifically, insights into the genetics of PROs will ultimately allow early identification of patients susceptible to PRO deficits, as well as the targeting of care in advance. Therefore, by unraveling the genetic understandings of PROs (eg, what specific single-nucleotide polymorphisms, on which specific genes, are associated with pain), researchers will have a greater understanding of diagnosis and treatment management for an individual patient, an understanding that has the potential to lead to improved survival, PRO assessments, and health service delivery. However, to ensure that PROs play an effective complementary role to traditional clinical end points in personalized medicine, it is essential to understand the issues that are inherent in PRO data and to put in place processes to guide researchers and other stakeholders. We highlighted the need for a conceptual frame to incorporate PRO data in personalized medicine and reviewed methodological and analytical approaches that are relevant for the analysis and interpretation of PROs. Of note, some of the issues—including multiplicity problems, handling of missing values, and modeling approaches—that arise in genetic data analysis are also shared by PROs.35 This provides challenges and opportunities from the standpoint of application, as well as methodological research. Recent developments in the

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specialized areas of PROs and personalized medicine provide fertile opportunity to bring the two areas even closer, and to advance the way treatment is attuned and delivered to address patient care and needs. Finally, personalized medicine and PROs have attracted considerable attention from regulatory agencies. For example, the recent US Food and Drug Administration guidance on PROs for a label claim in clinical trials provides a roadmap for inclusion of PROs in a label claim.36 Similar efforts are also under way to establish the regulatory science for evaluating the strategies and outcomes for personalized medicine.37 ■ Author Disclosure Statement Dr Alemayehu and Dr Cappelleri are employees and stockholders of Pfizer Inc.

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genotyping error in genetic epidemiology studies: MDR1 (ABCB1) G2677/T/A as an example. Cancer Epidemiol Biomarkers Prev. 2007;16:1185-1192. 12. Bogardus ST Jr, Concato J, Feinstein AR. Clinical epidemiological quality in molecular genetic research: the need for methodological standards. JAMA. 1999;281:1919-1926. 13. Sprangers MAG, Sloan JA, Veenhoven R, et al. The establishment of the GENEQOL Consortium to investigate the genetic disposition of patient-reported quality-of-life outcomes. Twin Res Hum Genet. 2009;12:301-311. 14. Trusheim MR, Berndt ER, Douglas FL. Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers. Nat Rev Drug Discov. 2007;6:287-293. 15. Rosenberger WF, Sverdlov O. Handling covariates in the design of clinical trials. Stat Sci. 2008;23:404-419. 16. Mahajan R, Gupta K. Adaptive design clinical trials: methodology, challenges and prospect. Indian J Pharmacol. 2010;42:201-207. 17. Marko NF, Weil RJ. Mathematical modeling of molecular data in translational medicine: theoretical considerations. Sci Transl Med. 2010 Nov 3;2(56):56rv4. 18. Little RJA, Rubin DB. Statistical Analysis with Missing Data. 2nd ed. Hoboken, NJ: John Wiley and Sons; 2002. 19. Pujol A, Mosca R, Farrés J, Aloy P. Unveiling the role of network and systems biology in drug discovery. Trends Pharmacol Sci. 2010;31:115-123. 20. Wang R, Lagakos SW, Ware JH, et al. Statistics in medicine—reporting of subgroup analyses in clinical trials. N Engl J Med. 2007;357:2189-2194. 21. Fayers PM, Machin D. Quality of Life: The Assessment, Analysis and Interpretation of Patientreported Outcomes. 2nd ed. Chichester, England: John Wiley & Sons; 2007. 22. Fairclough DL. Design and Analysis of Quality of Life Studies in Clinical Trials. 2nd ed. Boca Raton, FL: Chapman & Hall/CRC; 2010. 23. Donaldson GW, Moinpour CM. Individual differences in quality-of-life treatment response. Med Care. 2002;40(6 suppl):III-39-III-53. 24. Hambleton RK, Swaminathan H, Rogers HJ. Fundamentals of Item Response Theory. Newbury Park, CA: Sage Publications; 1991. 25. Cella D, Gershon RC, Lai JS, Choi S. The future of outcomes measurement: item banking, tailored short-forms, and computerized adaptive assessment. Qual Life Res. 2007;16(suppl 1):133-141. 26. Panel on Handling Missing Data in Clinical Trials, National Research Council. The Prevention and Treatment of Missing Data in Clinical Trials. Washington, DC: National Academies Press; 2010. 27. Marquis P, Chassany O, Abetz L. A comprehensive strategy for the interpretation of qualityof-life data based on existing methods. Value Health. 2004;7:93-104. 28. McLeod LD, Coon CD, Martin SA, et al. Interpreting patient-reported outcome results: US FDA guidance and emerging methods. Expert Rev Pharmacoecon Outcomes Res. 2011;11:163-169. 29. Hays RD, Brodsky M, Francis M, et al. Evaluating the statistical significance of health-related quality-of-life change in individual patients. Eval Health Prof. 2005;28:160-171. 30. Wilson IB, Cleary PD. Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA. 1995;273:59-65. 31. Kent DM, Rothwell PM, Ioannidis JP, et al. Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal. Trials. 2010;11:85. 32. Kent DM, Hayward RA. Limitations of applying summary results of clinical trials to individual patients: the need for risk stratification. JAMA. 2007;298:1209-1212. 33. Dmitrienko A, Tamhane A, Bretz F, eds. Multiple Testing Problems in Pharmaceutical Statistics. Boca Raton, FL: Chapman & Hall/CRC; 2009. 34. Donaldson G. Patient-reported outcomes and the mandate of measurement. Qual Life Res. 2008;7:1303-1313. 35. Mayo MS, Gajewski BJ, Morris JS. Some statistical issues in microarray gene expression data. Radiat Res. 2006;165:745-748. 36. US Food and Drug Administration. Guidance for industry on patient-reported outcome measures: use in medical product development to support labeling claims. Federal Register. 2009;74:65132-65133. 37. US Food and Drug Administration. Building the infrastructure to drive and support personalized medicine. www.fda.gov/AboutFDA/ReportsManualsForms/Reports/ ucm274440.htm. Accessed July 25, 2012.

STAKEHOLDER PERSPECTIVE No Physician Treats an Average Patient: Bridging the Gap between Group-Based Data and Patient-Specific Treatment Outcomes It has been suggested that researchers live at the mean, whereas clinicians live in the standard deviation. This often-cited nostrum reflects a general sentiment that data that are derived on a group level frequently map poorly to treatment outcomes for individual patients who have unique genetic and phenotypic signatures that modify and mediate treatment response. The review article by Alemayehu and Cappelleri is an attempt to bridge this gap by providing a methodological substrate for the use of patient-reported outcomes (PROs) in the evaluation of novel therapy. The recom-

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mended approaches ensure that the evidence for efficacy, safety, and utility that are usually filtered through the perception of a clinician can be expressed on a patientspecific basis. Implications for researchers, payers, and patients are derived from this approach. RESEARCHERS: A pathway toward personalized medicine represents a sequence of research opportunities ranging from target validation, investigation of pharmacokinetic/pharmacodynamic relationships, description of modifiers of safety and efficacy, stratification of populations based on anticipated response, and

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STAKEHOLDER PERSPECTIVE (Continued) finally, the ability to characterize treatment effects in easily interpretable constructs, given known patientspecific variables. Within this mosaic, the inclusion of PROs in prospective, interventional research can be considered an end point for a number of antecedent activities, which capture a patient’s perceptions of a broad spectrum of disease and treatment outcomes. As in other reviews,1 the emphasis by Alemayehu and Cappelleri on longitudinal data analyses, adjustments for missing data, and the need for clearly articulated concepts and actionable information is noteworthy. Indeed, the ability to incorporate PRO results into product labeling reflects attention to “fit-for-purpose” issues (ie, content validity, recall, cross-cultural validation) and experimental design (ie, potential bias, clinical meaningfulness, missing data),2 which are addressed within this review. Among the design elements that must be considered in a research program are the lack of generalizability of trial participants, the variety of PRO measures encountered (eg, 14 in chronic heart failure3), and potential discrepancies in physician- versus patient-reported assessments, which are based on the source of the data and the nature of the outcomes.4,5 Differences in maturation rates for physician-reported outcomes versus PROs can also be noted, even if they are ultimately concordant.6 Mixtures of positive and negative PRO results can occur when contrasting treatment versus control as a reflection of the pharmacologic properties of the intervention. Therefore, the position of PROs in a hierarchy of measures and outcomes must be approached within a clear conceptual framework, as suggested in this review, to adjudicate possible qualitative or quantitative treatment interactions across measures. PAYERS: Large-scale population trials may ignore genetic and environmental exposure differences across individuals that influence response, yet financial and regulatory models exist in a framework of these data. The emphasis on PROs (including functional status, psychological well-being, treatment hearings, and satisfaction) brings with it an implied stratification of treatment based on prognostically important variables which places new demands for innovative payer interface with providers. For example, the PRO construct may imply a risk-assessment decision-support algorithm in which static metrics (eg, current disease characteristics, genotype, medical history) are integrated with basic lifestyle planning, advanced dynamic metrics (eg, targeted proteomic and gene expression labo-

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ratory profiles), and personalized health interventions, including tailored pharmaceutical interventions.7 Predictive modeling capabilities move payers beyond mediators in a transaction to key participants in clinical decisions regarding risk stratification and treatment planning. Similarly, reimbursement and authorization decisions can be based on information derived from group data expressed as the proportion of patients who achieved a clinically important response on a PRO (eg, the number needed to treat). Precedence for requiring specific improvements in discrete outcomes for individual patients after treatment initiation already exists.8 Finally, the links between PROs and economic outcomes (both examples of healthcare outcomes) are often tenuous, even for well-established, high-visibility chronic illnesses, such as type 2 diabetes,9 which offers impetus for future payer-sponsored research. PATIENTS: PROs exemplify the emergence of predictive, preventive, personalized, and participatory medicine (together known as “P4 medicine”).10 Rather than being passive recipients of care, patient data that are generated in the context of a clinical trial, and then later in a commercial environment, can help adapt treatment decisions to particular patient circumstances. As an example, the prevalence of PROs in a patientcentered online platform suggests that web-based data entry can be a useful source for hypothesis generation.11 Michael F. Murphy, MD, PhD Chief Medical Officer and Scientific Officer Worldwide Clinical Trials 1. Revicki DA, Erickson PA, Sloan JA, et al. Interpreting and reporting results based on patientreported outcomes. Value Health. 2007;10 (suppl 2):S116-S124. 2. DeMuro C, Clark M, Mordin M, et al. Reasons for rejection of patient-reported outcome label claims: a compilation based on a review of patient-reported outcome use among new molecular entities and biologic license applications, 2006-2010. Value Health. 2012;15:443-448. 3. Chang S, Gholizadeh L, Salamonson Y, et al. Health span or life span: the role of patientreported outcomes in informing health policy. Health Policy. 2011;100:96-104. 4. Cobden DS, Niessen LW, Barr CB, et al. Relationships among self-management, patient perceptions of care, and health economic outcomes for decision-making and clinical practice in type 2 diabetes. Value Health. 2010;13:138-147. 5. Neben-Wittich MA, Atherton PJ, Schwartz DJ, et al. Comparison of provider-assessed and patient-reported outcome measures of acute skin toxicity during a phase III trial of mometasone cream versus placebo during breast radiotherapy: the North Central Cancer Treatment Group (N06C4). Int J Radiat Oncol Biol Phys. 2011;81:397-402. 6. Poole CD, Connolly MP, Nielsen SK, et al. A comparison of physician-rated disease severity and patient reported outcomes in mild to moderately active ulcerative colitis. J Crohns Colitis. 2010;4:275-282. 7. Langheier JM, Snyderman R. Prospective medicine: the role for genomics in personalized health planning. Pharmacogenomics. 2004;5:1-8. 8. Blue Cross of California. Medicare part D coverage criteria. AMPYRA (dalfampridine). January 2012. www.blueshieldca.com/sites/medicare/documents/PA_CY2012_AMPYRA_ dalfampridine_MCweb.pdf. Accessed August 13, 2012. 9. Vieta A, Badia X, Sacristán JA. A systematic review of patient-reported and economic outcomes: value to stakeholders in the decision-making process in patients with type 2 diabetes mellitus. Clin Ther. 2011;33:1225-1245. 10. Hood L, Balling R, Auffray C. Revolutionizing medicine in the 21(st) century through systems approaches. Biotechnol J. 2012;7:992-1001. 11. Frost J, Okun S, Vaughan T, et al. Patient-reported outcomes as a source of evidence in offlabel prescribing: analysis of data from PatientsLikeMe. J Med Internet Res. 2011;13:e6.

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Constipation Dyspepsia

5.3 0.9 1.7 5.2 0.9 2.6 Add-on to Metformin + Glimepiride Placebo + Metformin + Glargine + Metformin Victoza® 1.8 + + Glimepiride Glimepiride Metformin + N = 232 N = 114 Glimepiride N = 230 (%) (%) (%) Adverse Event Term Nausea 13.9 3.5 1.3 Diarrhea 10.0 5.3 1.3 Headache 9.6 7.9 5.6 Dyspepsia 6.5 0.9 1.7 Vomiting 6.5 3.5 0.4 Add-on to Metformin + Rosiglitazone All Victoza® + Metformin + Placebo + Metformin Rosiglitazone N = 355 + Rosiglitazone N = 175 (%) (%) Adverse Event Term Nausea 34.6 8.6 Diarrhea 14.1 6.3 Vomiting 12.4 2.9 Decreased Appetite 9.3 1.1 Anorexia 9.0 0.0 Headache 8.2 4.6 Constipation 5.1 1.1 Fatigue 5.1 1.7 Table 3: Treatment-Emergent Adverse Events in 26 Week Open-Label Trial versus Exenatide (Adverse events with frequency ≥5% and occurring more frequently with Victoza® compared to exenatide are listed) Exenatide 10 mcg twice Victoza® 1.8 mg once daily + metformin and/or daily + metformin and/or sulfonylurea N = 232 sulfonylurea N = 235 (%) (%) Preferred Term Diarrhea 12.3 12.1 Dyspepsia 8.9 4.7 Constipation 5.1 2.6 Gastrointestinal adverse events: In the five clinical trials of 26 weeks duration or longer, gastrointestinal adverse events were reported in 41% of Victoza®-treated patients and were dose-related. Gastrointestinal adverse events occurred in 17% of comparator-treated patients. Events that occurred more commonly among Victoza®-treated patients included nausea, vomiting, diarrhea, dyspepsia and constipation. In a 26-week study of Victoza® versus exenatide, both in combination with metformin and/ or sulfonylurea overall gastrointestinal adverse event incidence rates, including nausea, were similar in patients treated with Victoza® and exenatide. In five clinical trials of 26 weeks duration or longer, the percentage of patients who reported nausea declined over time. Approximately 13% of Victoza®treated patients and 2% of comparator-treated patients reported nausea during the first 2 weeks of treatment. In a 26 week study of Victoza® versus exenatide, both in combination with metformin and/ or sulfonylurea, the proportion of patients with nausea also declined over time. Immunogenicity: Consistent with the potentially immunogenic properties of protein and peptide pharmaceuticals, patients treated with Victoza® may develop anti-liraglutide antibodies. Approximately 50-70% of Victoza®treated patients in the five clinical trials of 26 weeks duration or longer were tested for the presence of anti-liraglutide antibodies at the end of treatment. Low titers (concentrations not requiring dilution of serum) of anti-liraglutide antibodies were detected in 8.6% of these Victoza®-treated patients. Sampling was not performed uniformly across all patients in the clinical trials, and this may have resulted in an underestimate of the actual percentage of patients who developed antibodies. Crossreacting anti-liraglutide antibodies to native glucagon-like peptide-1 (GLP-1) occurred in 6.9% of the Victoza®-treated patients in the 52-week monotherapy trial and in 4.8% of the Victoza®-treated patients in the 26-week add-on combination therapy trials. These cross-reacting antibodies were not tested for neutralizing effect against native GLP-1, and thus the potential for clinically significant neutralization of native GLP-1 was not assessed. Antibodies that had a neutralizing effect on liraglutide in an in vitro assay occurred in 2.3% of the Victoza®-treated patients in the 52-week monotherapy trial and in 1.0% of the Victoza®-treated patients in the 26-week add-on combination therapy trials. Among Victoza®treated patients who developed anti-liraglutide antibodies, the most common category of adverse events was that of infections, which occurred among 40% of these patients compared to 36%, 34% and 35% of antibody-negative Victoza®-treated, placebo-treated and active-control-treated patients, respectively. The specific infections which occurred with greater frequency among Victoza®-treated antibody-positive patients were primarily nonserious upper respiratory tract infections, which occurred among 11% of Victoza®-treated antibody-positive patients; and among 7%, 7% and 5% of antibodynegative Victoza®-treated, placebo-treated and active-control-treated patients, respectively. Among Victoza®-treated antibody-negative patients, the most common category of adverse events was that of gastrointestinal events, which occurred in 43%, 18% and 19% of antibody-negative Victoza®-treated, placebo-treated and active-control-treated patients, respectively. Antibody formation was not associated with reduced efficacy of Victoza® when comparing mean HbA1c of all antibody-positive and all antibody-negative patients. However, the 3 patients with the highest titers of anti-liraglutide antibodies had no reduction in HbA1c with Victoza® treatment. In clinical trials of Victoza®, events from a composite of adverse events potentially related to immunogenicity (e.g. urticaria, angioedema) occurred among 0.8% of Victoza®-treated patients and among 0.4% of comparator-treated patients. Urticaria accounted for approximately one-half of the events in this composite for Victoza®-treated patients. Patients who developed anti-liraglutide antibodies were not more likely to develop events from the immunogenicity events composite than were patients who did not develop anti-liraglutide antibodies. Injection site reactions: Injection site reactions (e.g., injection site rash, erythema) were reported in approximately 2% of Victoza®-treated patients in the five clinical trials of at least 26 weeks duration. Less than 0.2% of Victoza®-treated patients discontinued due to injection site reactions. Papillary thyroid carcinoma: In clinical trials of Victoza®, there were 6 reported cases of papillary thyroid carcinoma in patients treated with Victoza® and 1 case in a comparator-treated patient (1.9 vs. 0.6 cases per 1000 patient-years). Most of these papillary thyroid carcinomas were <1 cm in greatest diameter and were diagnosed in surgical pathology specimens after thyroidectomy prompted by findings on protocol-specified screening with serum calcitonin or thyroid ultrasound. Hypoglycemia: In the clinical trials of at least 26 weeks

duration, hypoglycemia requiring the assistance of another person for treatment occurred in 7 Victoza®treated patients (2.6 cases per 1000 patient-years) and in two comparator-treated patients. Six of these 7 patients treated with Victoza® were also taking a sulfonylurea. One other patient was taking Victoza® in combination with metformin but had another likely explanation for the hypoglycemia (this event occurred during hospitalization and after insulin infusion) (Table 4). Two additional cases of hypoglycemia requiring the assistance of another person for treatment have subsequently been reported in patients who were not taking a concomitant sulfonylurea. Both patients were receiving Victoza®, one as monotherapy and the other in combination with metformin. Both patients had another likely explanation for the hypoglycemia (one received insulin during a frequently-sampled intravenous glucose tolerance test, and the other had intracranial hemorrhage and uncertain food intake). Table 4: Incidence (%) and Rate (episodes/patient year) of Hypoglycemia in the 52-Week Monotherapy Trial and in the 26-Week Combination Therapy Trials Victoza® Active Placebo Treatment Comparator Comparator Monotherapy Victoza® Glimepiride None (N = 497) (N = 248) Patient not able to self−treat 0 0 — Patient able to self−treat 9.7 (0.24) 25.0 (1.66) — Not classified 1.2 (0.03) 2.4 (0.04) — Placebo + Glimepiride + Add-on to Victoza® + Metformin Metformin Metformin Metformin (N = 121) (N = 242) (N = 724) Patient not able to self−treat 0.1 (0.001) 0 0 Patient able to self−treat 3.6 (0.05) 22.3 (0.87) 2.5 (0.06) Add-on to Glimepiride Victoza® + Placebo + Rosiglitazone + Glimepiride Glimepiride Glimepiride (N = 114) (N = 231) (N = 695) Patient not able to self−treat 0.1 (0.003) 0 0 Patient able to self−treat 7.5 (0.38) 4.3 (0.12) 2.6 (0.17) Not classified 0.9 (0.05) 0.9 (0.02) 0 Victoza® + Placebo + Add-on to None Metformin + Metformin + Metformin + Rosiglitazone Rosiglitazone Rosiglitazone (N = 175) (N = 355) Patient not able to self−treat 0 — 0 Patient able to self−treat 7.9 (0.49) — 4.6 (0.15) Not classified 0.6 (0.01) — 1.1 (0.03) Placebo + Add-on to Victoza® + Insulin glargine Metformin + Metformin + Glimepiride + Metformin + Metformin + Glimepiride Glimepiride Glimepiride (N = 114) (N = 232) (N = 230) Patient not able to self−treat 2.2 (0.06) 0 0 Patient able to self−treat 27.4 (1.16) 28.9 (1.29) 16.7 (0.95) Not classified 0 1.7 (0.04) 0 In a pooled analysis of clinical trials, the incidence rate (per 1,000 patient-years) for malignant neoplasms (based on investigator-reported events, medical history, pathology reports, and surgical reports from both blinded and open-label study periods) was 10.9 for Victoza®, 6.3 for placebo, and 7.2 for active comparator. After excluding papillary thyroid carcinoma events [see Adverse Reactions], no particular cancer cell type predominated. Seven malignant neoplasm events were reported beyond 1 year of exposure to study medication, six events among Victoza®-treated patients (4 colon, 1 prostate and 1 nasopharyngeal), no events with placebo and one event with active comparator (colon). Causality has not been established. Laboratory Tests: In the five clinical trials of at least 26 weeks duration, mildly elevated serum bilirubin concentrations (elevations to no more than twice the upper limit of the reference range) occurred in 4.0% of Victoza®-treated patients, 2.1% of placebo-treated patients and 3.5% of active-comparator-treated patients. This finding was not accompanied by abnormalities in other liver tests. The significance of this isolated finding is unknown. Post-Marketing Experience: The following additional adverse reactions have been reported during post-approval use of Victoza®. Because these events are reported voluntarily from a population of uncertain size, it is generally not possible to reliably estimate their frequency or establish a causal relationship to drug exposure. Gastrointestinal: nausea, vomiting and diarrhea sometimes resulting in dehydration [see Warnings and Precautions]. Renal and Urinary Disorders: increased serum creatinine, acute renal failure or worsening of chronic renal failure, which may sometimes require hemodialysis [see Warnings and Precautions]. OVERDOSAGE: In a clinical trial, one patient with type 2 diabetes experienced a single overdose of Victoza® 17.4 mg subcutaneous (10 times the maximum recommended dose). Effects of the overdose included severe nausea and vomiting requiring hospitalization. No hypoglycemia was reported. The patient recovered without complications. In the event of overdosage, appropriate supportive treatment should be initiated according to the patient’s clinical signs and symptoms. More detailed information is available upon request. For information about Victoza® contact: Novo Nordisk Inc., 100 College Road West, Princeton, New Jersey 08540, 1−877-484-2869 Date of Issue: May 18, 2011 Version: 3 Manufactured by: Novo Nordisk A/S, DK-2880 Bagsvaerd, Denmark Victoza® is a registered trademark of Novo Nordisk A/S. Victoza® is covered by US Patent Nos. 6,268,343; 6,458,924; and 7,235,627 and other patents pending. Victoza® Pen is covered by US Patent Nos. 6,004,297; 6,235,004; 6,582,404 and other patents pending. © 2011 Novo Nordisk 140586-R3 6/2011


Help adult patients with type 2 diabetes gain greater access

Get to know Victoza® on a deeper level. Powerful reductions in A1C from -0.8% to -1.5%*

Low rate of hypoglycemia

Flexible dosing any time of day, independent of meals

May reduce weight

VictozaCare™ helps patients stay on track with ongoing support

—Victoza® is not indicated for the management of obesity, and weight change was a secondary end point in clinical trials

—Patients enrolled in VictozaCare™ were more adherent to Victoza® than those not enrolled†

To see how Victoza® works for your patients, visit VictozaPro.com/GLP1.

Indications and usage Victoza® is indicated as an adjunct to diet and exercise to improve glycemic control in adults with type 2 diabetes mellitus. Because of the uncertain relevance of the rodent thyroid C-cell tumor findings to humans, prescribe Victoza® only to patients for whom the potential benefits are considered to outweigh the potential risk. Victoza® is not recommended as first-line therapy for patients who have inadequate glycemic control on diet and exercise. In clinical trials of Victoza®, there were more cases of pancreatitis with Victoza® than with comparators. Victoza® has not been studied sufficiently in patients with a history of pancreatitis to determine whether these patients are at increased risk for pancreatitis while using Victoza®. Use with caution in patients with a history of pancreatitis. Victoza® is not a substitute for insulin. Victoza® should not be used in patients with type 1 diabetes mellitus or for the treatment of diabetic ketoacidosis, as it would not be effective in these settings. ®

The concurrent use of Victoza and insulin has not been studied.

Important safety information Liraglutide causes dose-dependent and treatment-durationdependent thyroid C-cell tumors at clinically relevant exposures in both genders of rats and mice. It is unknown whether Victoza® causes thyroid C-cell tumors, including medullary thyroid carcinoma (MTC), in humans, as human relevance could not be ruled out by clinical or nonclinical studies. Victoza® is contraindicated in patients with a personal or family history of MTC and in patients with Multiple Endocrine Neoplasia syndrome type 2 (MEN 2). Based on the findings in rodents, monitoring with serum calcitonin or thyroid ultrasound was performed during clinical trials, but this may have increased the number of unnecessary thyroid surgeries. It is unknown whether monitoring with serum Victoza® is a registered trademark and VictozaCare™ is a trademark of Novo Nordisk A/S.

calcitonin or thyroid ultrasound will mitigate human risk of thyroid C-cell tumors. Patients should be counseled regarding the risk and symptoms of thyroid tumors. If pancreatitis is suspected, Victoza® should be discontinued. Victoza® should not be re-initiated if pancreatitis is confirmed. When Victoza® is used with an insulin secretagogue (e.g. a sulfonylurea) serious hypoglycemia can occur. Consider lowering the dose of the insulin secretagogue to reduce the risk of hypoglycemia. Renal impairment has been reported postmarketing, usually in association with nausea, vomiting, diarrhea, or dehydration, which may sometimes require hemodialysis. Use caution when initiating or escalating doses of Victoza® in patients with renal impairment. There have been no studies establishing conclusive evidence of macrovascular risk reduction with Victoza® or any other antidiabetic drug. The most common adverse reactions, reported in ≥5% of patients treated with Victoza® and more commonly than in patients treated with placebo, are headache, nausea, diarrhea, and anti-liraglutide antibody formation. Immunogenicity-related events, including urticaria, were more common among Victoza®-treated patients (0.8%) than among comparator-treated patients (0.4%) in clinical trials. Victoza® has not been studied in type 2 diabetes patients below 18 years of age and is not recommended for use in pediatric patients. Victoza® should be used with caution in patients with hepatic impairment. Please see brief summary of Prescribing Information on adjacent page. *Victoza® 1.2 mg and 1.8 mg when used alone or in combination with OADs. † Crossix ScoreBoard™ Report, September 2011. Adherence measured by number of actual Victoza® prescriptions filled for existing Victoza® patients enrolled in VictozaCare™ versus a match-pair control group not enrolled in VictozaCare™ through first 8 months of enrollment.

© 2012 Novo Nordisk

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