Schottenfeld and Fraumeni Cancer Epidemiology and Prevention
Fourth Edition
Lead Editor
MICHAEL J. THUN, MD, MS
Epidemiology and Surveillance Research (Retired)
American Cancer Society
Atlanta, Georgia
Co-Editors
MARTHA S. LINET, MD, MPH
Division of Cancer Epidemiology and Genetics
National Cancer Institute
Bethesda, Maryland
JAMES R. CERHAN, MD, PHD
Department of Health Sciences Research
Mayo Clinic Rochester, Minnesota
CHRISTOPHER HAIMAN, SCD
Department of Preventive Medicine
Keck School of Medicine, University of Southern California Los Angeles, California
DAVID SCHOTTENFELD, MD, MSC
Department of Epidemiology (Retired) University of Michigan School of Public Health Ann Arbor, Michigan
Project Manager
ANNELIE M. LANDGREN, MPH, PMP
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© Oxford University Press 2018
Third Edition published 2006
Second edition published 1996
First edition published 1982
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Library of Congress Cataloging-in-Publication Data
Names: Thun, Michael J., editor. | Linet, Martha S., editor. | Cerhan, James R., editor. | Haiman, Christopher, editor. | Schottenfeld, David, editor. Title: Schottenfeld and Fraumeni Cancer Epidemiology and Prevention / lead editor, Michael J. Thun ; co-editors, Martha S. Linet, James R. Cerhan, Christopher Haiman, David Schottenfeld ; project manager, Annelie M. Landgren. Other titles: Cancer epidemiology and prevention
Description: Fourth edition. | New York, NY : Oxford University Press, [2018] | Preceded by Cancer epidemiology and prevention / edited by David Schottenfeld, Joseph F. Fraumeni Jr. 3rd ed. 2006. | Includes bibliographical references and index. Identifiers: LCCN 2017038170 | ISBN 9780190238667 (hardcover : alk. paper) Subjects: | MESH: Neoplasms—epidemiology | Neoplasms—prevention & control Classification: LCC RA645.C3 | NLM QZ 220.1 | DDC 614.5/999—dc23
LC record available at https://lccn.loc.gov/2017038170
9 8 7 6 5 4 3 2 1
Printed by Sheridan Books, Inc., United States of America
Acknowledgments ix Contributors xi Preface xix
1. Introduction 1 Michael J. Thun, Martha S. Linet, James R. Cerhan, Christopher A. Haiman, and David Schottenfeld
I BASIC CONCEPTS
2. Biology of Neoplasia 9 Michael Dean and Karobi Moitra
3. Morphological and Molecular Classification of Human Cancer 19 Mark E. Sherman, Melissa A. Troester, Katherine A. Hoadley, and William F. Anderson
4. Genomic Landscape of Cancer: Insights for Epidemiologists 43 Christopher J. Maher and Elaine R. Mardis
5. Genetic Epidemiology of Cancer 53 Kathryn L. Penney, Kyriaki Michailidou, Deanna Alexis Carere, Chenan Zhang, Brandon Pierce, Sara Lindström, and Peter Kraft
6. Application of Biomarkers in Cancer Epidemiology 77 Roel Vermeulen, Douglas A. Bell, Dean P. Jones, Montserrat Garcia-Closas, Avrum Spira, Teresa W. Wang, Martyn T. Smith, Qing Lan, and Nathaniel Rothman
7. Causal Inference in Cancer Epidemiology 97 Steven N. Goodman and Jonathan M. Samet
II THE MAGNITUDE OF CANCER
8. Patterns of Cancer Incidence, Mortality, and Survival 107 Ahmedin Jemal, D. Maxwell Parkin, and Freddie Bray
9. Socioeconomic Disparities in Cancer Incidence and Mortality 141 Candyce Kroenke and Ichiro Kawachi
10. The Economic Burden of Cancer in the United States 169 K. Robin Yabroff, Gery P. Guy Jr., Matthew P. Banegas, and Donatus U. Ekwueme
11. Tobacco
Michael J. Thun and Neal D. Freedman
12. Alcohol and Cancer Risk
Susan M. Gapstur and Philip John Brooks
13. Ionizing Radiation 227
Amy Berrington de González, André Bouville, Preetha Rajaraman, and Mary Schubauer-Berigan
14. Ultraviolet Radiation
Adèle C. Green and David C. Whiteman
15. Electromagnetic Fields
Maria Feychting and Joachim Schüz
16. Occupational Cancer
Kyle Steenland, Shelia Hoar Zahm, and A. Blair
17. Air Pollution
Jonathan M. Samet and Aaron J. Cohen
18. Water Contaminants
Kenneth P. Cantor, Craig M. Steinmaus, Mary H. Ward, and Laura E. Beane Freeman
19. Diet and Nutrition 329
Marjorie L. McCullough and Walter C. Willett
20. Obesity and Body Composition 351
NaNa Keum, Mingyang Song, Edward L. Giovannucci, and A. Heather Eliassen
21. Physical Activity, Sedentary Behaviors, and Risk of Cancer 377
Steven C. Moore, Charles E. Matthews, Sarah Keadle, Alpa V. Patel, and I-Min Lee
22. Hormones and Cancer
Robert N. Hoover, Amanda Black, and Rebecca Troisi
23. Pharmaceutical Drugs Other Than Hormones
Marie C. Bradley, Michael A. O’Rorke, Janine A. Cooper, Søren Friis, and Laurel A. Habel
24. Infectious Agents 433
Silvia Franceschi, Hashem B. El-Serag, David Forman, Robert Newton, and Martyn Plummer
25. Immunologic Factors
Eric A. Engels and Allan Hildesheim
IV CANCERS BY TISSUE OF ORIGIN
26. Nasopharyngeal Cancer
Ellen T. Chang and Allan Hildesheim
27. Cancer of the Larynx
Andrew F. Olshan and Mia Hashibe
28. Lung Cancer
Michael J. Thun, S. Jane Henley, and William D. Travis
29. Oral Cavity, Oropharynx, Lip, and Salivary Glands
Mia Hashibe, Erich M. Sturgis, Jacques Ferlay, and Deborah M. Winn
30. Esophageal Cancer
William J. Blot and Robert E. Tarone
31. Stomach Cancer 593
Catherine de Martel and Julie Parsonnet
32. Cancer of the Pancreas 611
Samuel O. Antwi, Rick J. Jansen, and Gloria M. Petersen
33. Liver Cancer 635
W. Thomas London, Jessica L. Petrick, and Katherine A. McGlynn
34. Biliary Tract Cancer 661
Jill Koshiol, Catterina Ferreccio, Susan S. Devesa, Juan Carlos Roa, and Joseph F. Fraumeni, Jr.
35. Small Intestine Cancer 671
Jennifer L. Beebe-Dimmer, Fawn D. Vigneau, and David Schottenfeld
36. Cancers of the Colon and Rectum 681
Kana Wu, NaNa Keum, Reiko Nishihara, and Edward L.Giovannucci
37. Anal Cancer 707
Andrew E. Grulich, Fengyi Jin, and I. Mary Poynten
38. Leukemias 715
Martha S. Linet, Lindsay M. Morton, Susan S. Devesa, and Graça M. Dores
39. Hodgkin Lymphoma 745
Henrik Hjalgrim, Ellen T. Chang, and Sally L. Glaser
40. The Non-Hodgkin Lymphomas 767
James R. Cerhan, Claire M. Vajdic, and John J. Spinelli
41. Multiple Myeloma 797
Mark P. Purdue, Jonathan N. Hofmann, Elizabeth E. Brown, and Celine M. Vachon
42. Bone Cancers 815
Lisa Mirabello, Rochelle E. Curtis, and Sharon A. Savage
43. Soft Tissue Sarcoma 829
Marianne Berwick and Charles Wiggins
44. Thyroid Cancer 839
Cari M. Kitahara, Arthur B. Schneider, and Alina V. Brenner
45. Breast Cancer 861
Louise A. Brinton, Mia M. Gaudet, and Gretchen L. Gierach
46. Ovarian Cancer 889 Shelley S. Tworoger, Amy L. Shafrir, and Susan E. Hankinson
47. Endometrial Cancer 909 Linda S. Cook, Angela L. W. Meisner, and Noel S. Weiss
48. Cervical Cancer 925 Rolando Herrero and Raul Murillo
49. Vulvar and Vaginal Cancers 947 Margaret M. Madeleine and Lisa G. Johnson
50. Choriocarcinoma 953
Julie R. Palmer
51. Renal Cancer 961
Wong-Ho Chow, Ghislaine Scelo, and Robert E. Tarone
52. Bladder Cancer 977
Debra T. Silverman, Stella Koutros, Jonine D. Figueroa, Ludmila Prokunina-Olsson, and Nathaniel Rothman
53. Prostate Cancer 997
Catherine M. Tangen, Marian L. Neuhouser, and Janet L. Stanford
54. Testicular Cancer 1019
Katherine A. McGlynn, Ewa Rajpert-De Meyts, and Andreas Stang
55. Penile Cancer 1029
Morten Frisch
56. Nervous System 1039
E. Susan Amirian, Quinn T. Ostrom, Yanhong Liu, Jill Barnholtz-Sloan, and Melissa L. Bondy
57. Melanoma 1061
Bruce K. Armstrong, Claire M. Vajdic, and Anne E. Cust
58. Keratinocyte Cancers 1089
Anala Gossai, Dorothea T. Barton, Judy R. Rees, Heather H. Nelson, and Margaret R. Karagas
59. Childhood Cancers 1119
Eve Roman, Tracy Lightfoot, Susan Picton, and Sally Kinsey
60. Multiple Primary Cancers 1155
Lindsay M. Morton, Sharon A. Savage, and Smita Bhatia
V CANCER PREVENTION AND CONTROL
61. Framework for Understanding Cancer Prevention 1193
Michael J. Thun, Christopher P. Wild, and Graham Colditz
62. Primary Prevention of Cancer 1205
62.1. Tobacco Control 1207
Jeffrey Drope, Clifford E. Douglas, and Brian D. Carter
62.2. Prevention of Obesity and Physical Inactivity 1211
Ambika Satija and Frank B. Hu
62.3. Prevention of Infection-Related Cancers 1217
Marc Bulterys, Julia Brotherton, and Ding-Shinn Chen
62.4. Protection from Ultraviolet Radiation 1221
Robyn M. Lucas, Rachel E. Neale, Peter Gies, and Terry Slevin
62.5. Preventive Therapy 1229
Jack Cuzick
62.6. Regulation 1239
Jonathan M. Samet and Lynn Goldman
63. Cancer Screening 1255
Jennifer M. Croswell, Russell P. Harris, and Barnett S. Kramer
Index 1271
Acknowledgments
We are indebted to the more than 190 chapter authors who generously contributed their time, labor, and expertise to produce this comprehensively updated fourth edition. The multi-authored text reflects the increasingly interdisciplinary and collaborative nature of the field; it provides a resource for researchers seeking to harness the unprecedented advances in genetic and molecular research into large-scale population studies of cancer etiology, and ultimately into effective preventive interventions. We owe special thanks to Ms. Annelie Landgren, whose energy, enthusiasm, and organizational expertise as project manager have been invaluable in bringing this text to completion. We also thank Dr. Stephen Chanock for his early and unfailing encouragement and for supporting the critical infrastructure necessary for such a collaborative enterprise. This book would not have been possible without the generous forbearance of our spouses and families. Finally, Michael Thun thanks Dr. Lynne Moody for her insights as a sounding board throughout this process.
Contributors
E. Susan Amirian, PhD
Dan L Duncan Cancer Center Baylor College of Medicine Houston, Texas
William F. Anderson, MD, MPH Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Samuel O. Antwi, PhD Department of Health Sciences Research Mayo Clinic College of Medicine Rochester, Minnesota
Bruce K. Armstrong, MD, PhD* School of Public Health
The University of Sydney Sydney, New South Wales, Australia
Matthew P. Banegas, PhD, MPH Center for Health Research Kaiser Permanente Portland, Oregon
Jill Barnholtz-Sloan, PhD Case Comprehensive Cancer Center Case Western Reserve University School of Medicine Cleveland, Ohio
Dorothea T. Barton, MD Department of Surgery Dartmouth-Hitchcock Medical Center Lebanon, New Hampshire
Laura E. Beane Freeman, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
* Retired
Jennifer L. Beebe-Dimmer, PhD, MPH
Wayne State University School of Medicine Karmanos Cancer Institute Detroit, Michigan
Douglas A. Bell, PhD
Environmental Epigenomics, Immunity, Inflammation and Disease Laboratory
National Institute of Environmental Health Sciences Research Triangle Park, North Carolina
Amy Berrington de González, DPhil Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Marianne Berwick, PhD Department of Internal Medicine University of New Mexico Albuquerque, New Mexico
Smita Bhatia, MD, MPH Institute of Cancer Outcomes and Survivorship University of Alabama at Birmingham, School of Medicine Birmingham, Alabama
Amanda Black, PhD, MPH Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
A. Blair, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
William J. Blot, PhD Vanderbilt-Ingram Cancer Center Nashville, Tennessee
Melissa L. Bondy, PhD
Department of Medicine, Section of Epidemiology and Population Sciences
Baylor College of Medicine Houston, Texas
AndrÉ Bouville, PhD* Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Marie C. Bradley, PhD, MScPH Division of Cancer Control and Population Sciences National Cancer Institute Bethesda, Maryland
Freddie Bray, PhD
Section of Cancer Surveillance International Agency for Research on Cancer Lyon, France
Alina V. Brenner, MD, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Louise A. Brinton, PhD Division of Cancer Epidemiology and Genetics
National Cancer Institute Bethesda, Maryland
Philip John Brooks, PhD Laboratory of Neurogenetics
National Institute on Alcohol Abuse and Alcoholism, NIH Bethesda, Maryland
Julia Brotherton, MD, PhD
National HPV Vaccination Program Register Victorian Cytology Service East Melbourne, Victoria, Australia
Elizabeth E. Brown, PhD, MPH Department of Pathology University of Alabama at Birmingham Birmingham, Alabama
Marc Bulterys, MD, PhD HIV/Hepatitis Department World Health Organization Geneva, Switzerland
Kenneth P. Cantor, PhD, MPH* Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Deanna Alexis Carere, ScD, CGC Department of Pathology and Molecular Medicine McMaster University Hamilton, Ontario, Canada
Brian D. Carter, MPH Epidemiology Research Program
American Cancer Society Atlanta, Georgia
* Retired
‡ Consultant/Contractor
James R. Cerhan, MD, PhD, (Editor) Department of Health Sciences Research Mayo Clinic Rochester, Minnesota
Ellen T. Chang, ScD Center for Health Sciences Exponent Inc. Menlo Park, California
Ding-Shinn Chen, MD Hepatitis Research Center
National Taiwan University Hospital Taipei, Taiwan
Wong-Ho Chow, PhD Department of Epidemiology
The University of Texas MD Anderson Cancer Center Houston, Texas
Aaron J. Cohen, MPH, DSc‡ Health Effects Institute Boston, Massachusetts
Graham Colditz, MD, DrPH Division of Public Health Services Washington University St. Louis, Missouri
Linda S. Cook, PhD Department of Internal Medicine University of New Mexico Albuquerque, New Mexico
Janine A. Cooper, PhD School of Pharmacy Queen’s University Belfast Belfast, Northern Ireland
Jennifer M. Croswell, MD, MPH Patient-Centered Outcomes Research Institute Washington, DC
Rochelle E. Curtis, MA Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Anne E. Cust, PhD School of Public Health and Melanoma Institute Australia The University of Sydney Sydney, New South Wales, Australia
Jack Cuzick, PhD Wolfson Institute of Preventive Medicine
Queen Mary University of London London, United Kingdom
Catherine de Martel, MD, PhD Infections and Cancer Epidemiology Group International Agency for Research on Cancer Lyon, France
Michael Dean, PhD
Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Susan S. Devesa, PhD* Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Graça M. Dores, MD§ Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Clifford E. Douglas, JD Center for Tobacco Control American Cancer Society Atlanta, Georgia
Jeffrey Drope, PhD Economic & Health Policy Research American Cancer Society Atlanta, Georgia
Donatus U. Ekwueme, PhD, MS National Center for Chronic Disease Prevention and Health Promotion Centers for Disease Control and Prevention Atlanta, Georgia
A. Heather Eliassen, ScD Brigham & Women’s Hospital and Harvard Medical School Harvard TH Chan School of Public Health Boston, Massachusetts
Hashem B. El-Serag, MD, MPH Gastroenterology and Hepatology Baylor College of Medicine Houston, Texas
Eric A. Engels, MD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Jacques Ferlay, MSc Section of Cancer Surveillance International Agency for Research on Cancer Lyon, France
Catterina Ferreccio, MD, MPH Division of Public Health and Family Medicine School of Medicine, Pontificia Universidad Católica de Chile Santiago, Chile
Maria Feychting, PhD Institute of Environmental Medicine Karolinska Institutet Stockholm, Sweden
Jonine D. Figueroa, PhD
Usher Institute of Population Health Sciences and Informatics, CRUK Edinburgh Centre University of Edinburgh Edinburg, United Kingdom
* Retired
§ Adjunct
David Forman, PhD
International Agency for Research on Cancer Lyon, France
Silvia Franceschi, MD
International Agency for Research on Cancer Lyon, France
Joseph F. Fraumeni, Jr., MD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Neal D. Freedman, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Søren Friis, MD Statistics and Pharmacoepidemiology Danish Cancer Society Research Center Copenhagen, Denmark
Morten Frisch, MD, PhD, DrSci(Med) Department of Epidemiology Research Statens Serum Institut Copenhagen, Denmark
Susan M. Gapstur, PhD, MPH Epidemiology Research Program American Cancer Society Atlanta, Georgia
Montserrat Garcia-Closas, MD, DrPH Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Mia M. Gaudet, PhD Epidemiology Research Program American Cancer Society Atlanta, Georgia
Gretchen L. Gierach, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Peter Gies, PhD Australian Radiation Protection and Nuclear Safety Agency Melbourne, Victoria, Australia
Edward L. Giovannucci, MD, ScD Departments of Nutrition and Epidemiology Harvard TH Chan School of Public Health Boston, Massachusetts
Sally L. Glaser, PhD Cancer Prevention Institute of California Fremont, California
Lynn Goldman, MD, MS, MPH Milken Institute School of Public Health George Washington University Washington, DC
Steven N. Goodman, MD, PhD
Department of Medicine, Clinical and Translational Research
Stanford University School of Medicine Stanford, California
Anala Gossai, MPH, PhD Geisel School of Medicine Dartmouth College Hanover, New Hampshire
Adèle C. Green, MD, PhD Population Health Division
QIMR Berghofer Medical Research Institute Brisbane, Queensland, Australia
Andrew E. Grulich, PhD Kirby Institute
The University of New South Wales Sydney, New South Wales, Australia
Gery P. Guy Jr, PhD, MPH
National Center for Chronic Disease Prevention and Health Promotion
Centers for Disease Control and Prevention Atlanta, Georgia
Laurel A. Habel, PhD, MPH Division of Research
Kaiser Permanente Northern California Oakland, California
Christopher A. Haiman, ScD, (Editor) Department of Preventive Medicine
Keck School of Medicine of University of Southern California Los Angeles, California
Susan E. Hankinson, ScD Department of Biostatistics and Epidemiology University of Massachusetts Amherst, Massachusetts
Russell P. Harris, MD, MPH§ Lineberger Comprehensive Cancer Center University of North Carolina School of Medicine Chapel Hill, North Carolina
Mia Hashibe, PhD Department of Family and Preventive Medicine Huntsman Cancer Institute, University of Utah School of Medicine Salt Lake City, Utah
S. Jane Henley, MSPH Division of Cancer Prevention and Control
US Centers for Disease Control and Prevention Atlanta, Georgia
Rolando Herrero, MD, PhD Prevention and Implementation Group
International Agency for Research on Cancer Lyon, France
Allan Hildesheim, PhD Division of Cancer Epidemiology and Genetics
National Cancer Institute Bethesda, Maryland
§ adjunct
Henrik Hjalgrim, MD, PhD, DrSci(med) Department of Epidemiology Research Statens Serum Institut Copenhagen, Denmark
Katherine A. Hoadley, PhD Department of Genetics, Lineberger Comprehensive Cancer Center University of North Carolina at Chapel Hill Chapel Hill, North Carolina
Jonathan N. Hofmann, PhD Division of Cancer Epidemiology and Genetics
National Cancer Institute Bethesda, Maryland
Robert N. Hoover, MD, ScD Division of Cancer Epidemiology and Genetics
National Cancer Institute Bethesda, Maryland
Frank B. Hu, MD, PhD Departments of Nutrition and Epidemiology
Harvard TH Chan School of Public Health Boston, Massachusetts
Rick J. Jansen, MS, PhD Department of Public Health North Dakota State University Fargo, North Dakota
Ahmedin Jemal, DVM, PhD Surveillance and Health Services Research Program American Cancer Society Atlanta, Georgia
Fengyi Jin, PhD
Kirby Institute
The University of New South Wales Sydney, New South Wales, Australia
Lisa G. Johnson, PhD, MPH Division of Public Health Sciences
Fred Hutchinson Cancer Research Center Seattle, Washington
Dean P. Jones, PhD Department of Medicine Emory University Atlanta, Georgia
Margaret R. Karagas, PhD Department of Epidemiology
Geisel School of Medicine at Dartmouth Hanover, New Hampshire
Ichiro Kawachi, MD, PhD Department of Social and Behavioral Sciences
Harvard School of Public Health Boston, Massachusetts
Sarah Keadle, PhD, MPH Kinesiology Department California Polytechnic State University San Luis Obispo, California
NaNa Keum, ScD
Department of Nutrition
Harvard TH Chan School of Public Health Boston, Massachusetts
Sally Kinsey, MD, FRCP Department of Pediatric Hematology Leeds Teaching Hospitals NHS Trust Leeds, United Kingdom
Cari M. Kitahara, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Jill Koshiol, PhD
Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Stella Koutros, PhD Division of Cancer Epidemiology and Genetics
National Cancer Institute
Bethesda, Maryland
Peter Kraft, PhD Departments of Epidemiology and Biostatistics
Harvard TH Chan School of Public Health Boston, Massachusetts
Barnett S. Kramer, MD, MPH Division of Cancer Prevention National Cancer Institute Bethesda, Maryland
Candyce Kroenke, ScD, MPH Division of Research Kaiser Permanente Northern California Oakland, California
Qing Lan, MD, MPH Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
I-Min Lee, MBBS, ScD Brigham and Women’s Hospital Harvard Medical School Boston, Massachusetts
Tracy Lightfoot, PhD Department of Health Sciences University of York York, United Kingdom
Sara Lindström, PhD Department of Epidemiology University of Washington Seattle, Washington
Martha S. Linet, MD, MPH, (Editor) Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Yanhong Liu, PhD Department of Medicine, Section of Epidemiology and Population Sciences
Baylor College of Medicine Houston, Texas
W. Thomas London, MD* Fox Chase Cancer Center Philadelphia, Pennsylvania
Robyn M. Lucas, MBChB, MPH&TM, PhD Radiation Health Services Branch The Australian National University Canberra, The Australian Capital Territory, Australia
Margaret M. Madeleine, PhD Division of Public Health Sciences
Fred Hutchinson Cancer Research Center Seattle, Washington
Christopher J. Maher, PhD
McDonnell Genome Institute
Washington University School of Medicine
St. Louis, Missouri
Elaine R. Mardis, PhD McDonnell Genome Institute
Washington University School of Medicine St. Louis, Missouri
Charles E. Matthews, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Marjorie L. McCullough, ScD, RD Epidemiology Research Program American Cancer Society Atlanta, Georgia
Katherine A. McGlynn, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Angela L. W. Meisner, MPH New Mexico Tumor Registry University of New Mexico Albuquerque, New Mexico
Kyriaki Michailidou, PhD Department of Electron Microscopy/Molecular Pathology The Cyprus Institute of Neurology and Genetics Nicosia, Cyprus
Lisa Mirabello, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Karobi Moitra, PhD Trinity Washington University Washington, DC
* Retired
Steven C. Moore, PhD
Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Lindsay M. Morton, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Raul Murillo, MD Prevention and Implementation Group International Agency for Research on Cancer Lyon, France
Rachel E. Neale, PhD Population Health Division QIMR Berghofer Medical Research Institute Brisbane, Queensland, Australia
Heather H. Nelson, MPH, PhD Division of Epidemiology, Masonic Cancer Center University of Minnesota, Twin Cities Minneapolis, Minnesota
Marian L. Neuhouser, PhD Division of Public Health Sciences Fred Hutchinson Cancer Research Center Seattle, Washington
Robert Newton, PhD MRC/UVRI Uganda Research Unit Entebbe, Uganda
Reiko Nishihara, PhD Department of Pathology Brigham and Women’s Hospital Boston, Massachusetts
Michael A. O’Rorke, PhD School of Medicine Dentistry and Biomedical Sciences Queen’s University Belfast Belfast, Northern Ireland
Andrew F. Olshan, PhD Department of Epidemiology Gillings School of Global Public Health University of North Carolina Chapel Hill, North Carolina
Quinn T. Ostrom, MA, MPH Case Comprehensive Cancer Center Case Western Reserve University School of Medicine Cleveland, Ohio
Julie R. Palmer, ScD Slone Epidemiology Center at Boston University Boston, Massachusetts
D. Maxwell Parkin, MD, DSc Nuffield Department of Public Health University of Oxford Oxford, United Kingdom
Julie Parsonnet, MD Department of Medicine Stanford University School of Medicine Stanford, California
Alpa V. Patel, PhD
Epidemiology Research Program
American Cancer Society Atlanta, Georgia
Kathryn L. Penney, ScD ScD Department of Medicine
Brigham and Women’s Hospital / Harvard Medical School Boston, Massachusetts
Gloria M. Petersen, PhD Department of Health Sciences Research
Mayo Clinic College of Medicine Rochester, Minnesota
Jessica L. Petrick, PhD Division of Cancer Epidemiology and Genetics
National Cancer Institute Bethesda, Maryland
Susan Picton, BMBS, FRCPCH Department of Pediatric Oncology Leeds Teaching Hospitals NHS Trust Leeds, United Kingdom
Brandon Pierce, PhD Departments of Public Health Sciences and Human Genetics University of Chicago Chicago, Illinois
Martyn Plummer, PhD International Agency for Research on Cancer Lyon, France
I. Mary Poynten, PhD Kirby Institute
The University of New South Wales Sydney, New South Wales, Australia
Ludmila Prokunina-Olsson, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Mark P. Purdue, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Preetha Rajaraman, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Ewa Rajpert-De Meyts, MD, PhD Department of Growth & Reproduction Copenhagen University Hospital Rigshospitalet Copenhagen, Denmark
Judy R. Rees, BM, BCh, PhD Department of Epidemiology Geisel School of Medicine at Dartmouth Hanover, New Hampshire
Juan Carlos Roa, MD, Msc Department of Pathology School of Medicine, Pontificia Universidad Católica de Chile Santiago, Chile
Eve Roman, PhD
Department of Health Sciences University of York York, United Kingdom
Nathaniel Rothman, MD, MPH Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Jonathan M. Samet, MD Department of Preventive Medicine
Keck School of Medicine of University of Southern California Los Angeles, California
Ambika Satija, ScD Department of Nutrition
Harvard TH Chan School of Public Health Boston, Massachusetts
Sharon A. Savage, MD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Ghislaine Scelo, PhD Genetic Epidemiology Group International Agency for Research on Cancer Lyon, France
Arthur B. Schneider, MD, PhD* Section of Endocrinology, Diabetes and Metabolism University of Illinois at Chicago College of Medicine Chicago, Illinois
David Schottenfeld, MD, MSc (Editor)* Department of Epidemiology University of Michigan School of Public Health Ann Arbor, Michigan
Mary Schubauer-Berigan, PhD
Division of Surveillance Hazard Evaluation and Field Studies Centers for Disease Control and Prevention Atlanta, Georgia
Joachim Schüz, PhD Section of Environment and Radiation International Agency for Research on Cancer Lyon, France
Amy L. Shafrir, ScD Division of Adolescent and Young Adult Medicine Boston Children’s Hospital Boston, Massachusetts
Mark E. Sherman, MD Health Sciences Research
Mayo Clinic College of Medicine Jacksonville, Florida
Debra T. Silverman, ScD, ScM Division of Cancer Epidemiology and Genetics
National Cancer Institute Bethesda, Maryland
Terry Slevin, MPH Cancer Council Western Australia Perth, Western Australia, Australia
* Retired
Martyn T. Smith, PhD School of Public Health University of California at Berkeley Berkeley, California
Mingyang Song, MD, ScD Clinical and Translational Epidemiology Unit and Division of Gastroenterology
Massachusetts General Hospital and Harvard Medical School Boston, Massachusetts
John J. Spinelli, PhD Cancer Control Research British Columbia Cancer Agency Vancouver, British Columbia, Canada
Avrum Spira, MD, MSc Division of Computational Biomedicine Boston University School of Medicine Boston, Massachusetts
Janet L. Stanford, PhD Division of Public Health Sciences Fred Hutchinson Cancer Research Center Seattle, Washington
Andreas Stang, MD, MPH Institute of Medical Informatics, Biometry and Epidemiology University Hospital Essen Essen, Germany
Kyle Steenland, PhD
Rollins School of Public Health Emory University Atlanta, Georgia
Craig M. Steinmaus, MD, MPH School of Public Health University of California Berkeley Berkeley, California
Erich M. Sturgis, MD, MPH Department of Head and Neck Surgery
The University of Texas MD Anderson Cancer Center Houston, Texas
Catherine M. Tangen, DrPH Division of Public Health Sciences
Fred Hutchinson Cancer Research Center Seattle, Washington
Robert E. Tarone, PhD* International Epidemiology Institute Rockville, Maryland
Michael J. Thun, MD, MS (Editor)* Epidemiology and Surveillance Research American Cancer Society Atlanta, Georgia
William D. Travis, MD Department of Pathology Memorial Sloan Kettering Cancer Center New York, New York
Melissa A. Troester, PhD Department of Epidemiology Lineberger Comprehensive Cancer Center University of North Carolina at Chapel Hill Chapel Hill, North Carolina
Rebecca Troisi, ScD, MA
Division of Cancer Epidemiology and Genetics
National Cancer Institute
Bethesda, Maryland
Shelley S. Tworoger, PhD
Harvard Medical School and the Brigham and Women’s Hospital Harvard TH Chan School of Public Health Boston, Massachusetts
Celine M. Vachon, PhD Department of Health Sciences Research Mayo Clinic Rochester, Minnesota
Claire M. Vajdic, PhD
Centre for Big Data Research in Health University of New South Wales Sydney, New South Wales, Australia
Roel Vermeulen, PhD Institute for Risk Assessment Sciences Utrecht University Utrecht, The Netherlands
Fawn D. Vigneau, JD, MPH Wayne State University School of Medicine Karmanos Cancer Institute Detroit, Michigan
Teresa W. Wang, PhD Division of Computational Biomedicine Boston University School of Medicine Boston, Massachusetts
Mary H. Ward, PhD Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Noel S. Weiss, MD, DrPH Department of Epidemiology University of Washington Seattle, Washington
‡ Consultant/Contractor
David C. Whiteman, MD, PhD
Population Health Division
QIMR Berghofer Medical Research Institute Brisbane, Queensland, Australia
Charles Wiggins, PhD, MPH Department of Internal Medicine University of New Mexico Albuquerque, New Mexico
Christopher P. Wild, PhD Director’s Office
International Agency for Research on Cancer Lyon, France
Walter C. Willett, MD, DrPH Department of Nutrition
Harvard TH Chan School of Public Health Boston, Massachusetts
Deborah M. Winn, PhD Division of Cancer Control and Population Sciences
National Cancer Institute Bethesda, Maryland
Kana Wu, MD, PhD Department of Nutrition
Harvard TH Chan School of Public Health Boston, Massachusetts
K. Robin Yabroff, PhD Division of Cancer Control and Population Sciences
National Cancer Institute Bethesda, Maryland
Shelia Hoar Zahm, ScD‡ Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda, Maryland
Chenan Zhang, PhD Department of Epidemiology and Biostatistics University of California, San Francisco San Francisco, California
Preface
The Schottenfeld and Fraumeni text on Cancer Epidemiology and Prevention has served as the premier reference text for population research on the causes and prevention of cancers since the publication of the first edition in 1982 (Schottenfeld and Fraumeni, 1982). It is written for colleagues pursuing careers in research in cancer epidemiology and, more broadly, in preventive oncology. The founding editors, Dr. David Schottenfeld, now emeritus professor of epidemiology at the University of Michigan, and Dr. Joseph Fraumeni, recently retired as the director of the Division of Cancer Epidemiology and Genetics at the National Cancer Institute (NCI), updated their landmark text in 1996 and 2006 (Schottenfeld and Fraumeni, 1996, 2006).
The current edition again provides a comprehensive update of research advances in cancer epidemiology, prevention, and related fields in the past 10–15 years, and honors the founding editors in the title. The new editorial team is led by Dr. Michael Thun (editor-in-chief), formerly with the American Cancer Society, and includes four senior co-editors: Drs. Martha Linet from NCI, James Cerhan from the Mayo Clinic, Christopher Haiman from the University of Southern California, and David Schottenfeld. We are also deeply indebted to the internationally recognized experts who authored the 63 chapters. Without their generous effort and commitment, this updated synthesis would not be possible.
MICHAEL J. THUN, MARTHA S. LINET, JAMES R. CERHAN, CHRISTOPHER A. HAIMAN, AND DAVID SCHOTTENFELD
In this introduction, we provide an overview of the text and highlight cross-cutting developments and new opportunities that are transforming our understanding of the causes and prevention of cancer. As in previous editions, the text is grouped into five major parts: “Basic Concepts,” “The Magnitude of Cancer,” “The Causes of Cancer,” “Cancers by Tissue of Origin,” and “Cancer Prevention and Control.”
Part I first describes research advances in understanding “the biology of neoplasia,” including the progressive disruption of genetic and epigenetic controls that regulate cell growth, division, and survival (Chapter 2). Advances in high-throughput technologies have greatly expanded the ability to identify germline and somatic mutations and to relate these to etiology, prognosis, and treatment. Tumor classification is also changing for certain cancers, as data on the molecular features and lineage of the neoplastic cells is combined with information on the primary anatomic location and the morphologic, histopathologic and clinical characteristics of the tumor (Chapter 3). The “landscape” of genomic and epigenomic alterations in tumor tissue has been cataloged for multiple human cancers (Chapter 4), revealing both the singularity of individual cancer genomes and the commonality of genetic alterations that drive cancer in different tissues. Chapter 5 describes advances in research on inherited genomic variants that affect cancer risk. Genome-wide association studies (GWAS) have identified more than 700 germline loci associated with increased or decreased risk for various types of cancer, although the risk estimates for almost all are small to modest. Innovations in genomics and other “OMIC” technologies are identifying biomarkers that reflect internal exposures, biological processes, and intermediate outcomes in large population studies (Chapter 6). While research in many of these areas is still in its infancy, mechanistic and molecular insights are extending the traditional criteria for inferring causation in epidemiologic studies of cancer (Chapter 7).
Part 2 of the book discusses the global public health impact of cancer and its relationship to demographic trends, changing risk factors, socioeconomic disparities, and economic development. It considers the direct and indirect costs of cancer in the United States to illustrate the economic burden in a high income country. Parts 3–5 of the book discuss the growing list of exposures known to affect cancer risk, the epidemiology of over 30 types of cancer by tissue of origin, and the encouraging progress in cancer prevention and control. Major developments in these areas are discussed below, beginning with those that affect the public health impact of cancer.
MAJOR NEW DEVELOPMENTS
Global Trends in Cancer Risk and Burden
Part II, “The Magnitude of Cancer,” provides a global public health perspective on cancer. The human and economic costs of cancer are increasing worldwide (http://globocan.iarc.fr). The World Health Organization (WHO) estimates that 14 million new cases and 8.2 million deaths from cancer occurred in 2012. This burden is projected to increase to 24 million cases and 13 million deaths annually by 2035 (Ferlay et al., 2013). Chapter 8 decribes the disproportionate increase in the cancer burden in low- and middle-income countries (LMICs), which can least afford additional health-related, social and financial
costs. In 2012, these countries accounted for over half (57%) of all incident cancers; this is projected to increase to nearly two-thirds (65%) by 2035. Much of the increase will result from the growth and aging of populations, since LMICs currently comprise about 80% of the world’s population, and large numbers of young adults are now surviving to older ages, when cancer becomes more common. In addition to the effect of demographic changes, cancer incidence and mortality rates are increasing in LMICs because of the widespread adoption of Western patterns of diet, physical inactivity, excess body fat, delayed reproduction, and tobacco smoking, especially of manufactured cigarettes. As countries advance economically, the incidence rates of cancers traditionally associated with Westernization (e.g., breast, colorectum, lung, and prostate) increase more rapidly than the decrease in cancers caused partly or wholly by infectious agents (e.g., stomach, liver, uterine cervix). Survival after a diagnosis of cancer is also lower in LMICs than in high-resource countries, because of later stage at diagnosis, a higher proportion of tumors diagnosed clinically rather than incidentally, and limited access to standard and state-ofthe-art treatment protocols.
In economically developed countries, the incidence rates of most cancers are either stabilizing at a high level or decreasing, depending on the temporal trends of underlying risk factors and utilization of cancer screening. Despite the decreasing rates, the disease burden, or number of cancer cases and deaths, continues to increase. The increasing burden results from the aging and growth of populations, and the decline in competing causes of death from circulatory and infectious diseases. Mortality rates are decreasing more rapidly than incidence rates for many cancer sites due to a combination of prevention, early detection, and improvements in treatment.
Part III, “The Causes of Cancer,” discusses 15 broad categories of exposure that affect cancer risk. These include exposures that are typically considered “environmental” by the public (chemical carcinogens, ionizing radiation, occupational exposures, pollutants in air and drinking water), as well as exposures that are less widely recognized as carcinogenic (infectious agents, metabolic factors, body composition, reproductive and other hormones, pharmaceutical drugs, and immunological conditions). All of these exposures are “environmental” in the sense that they are acquired after conception rather than inherited. Some are genotoxic and damage the structure of DNA or alter DNA repair; others modify gene expression, induce oxidative stress and/ or chronic inflammation, suppress host immunity, immortalize cells, modulate receptors, and/or alter cell proliferation, cell death, or nutrient supply (Smith et al., 2016).
Although some exposures are conventionally perceived as “lifestyle choices”, they are by no means entirely voluntary. For example, behavioral risk factors such as tobacco smoking, energy imbalance, and physical inactivity are strongly influenced by factors in the social, economic, and cultural environment, beginning in early childhood. Physiologic addiction is a major driver of tobacco use at all ages.
Part IV of the book describes “Cancers by Tissue of Origin” for 33 anatomic sites, multiple primary tumors, and cancers in children. Rapid advances in discovering the molecular events that drive certain forms of cancer are transforming clinical diagnoses and treatment, and affecting tumor classification. This will influence future endpoints in etiologic studies and population-based cancer surveillance.
Part V, “Cancer Prevention and Control,” discusses the impact of interventions that effectively reduce carcinogenic exposures or disrupt the multistage progression of tumors. It focuses on interventions that demonstrably reduce cancer risk in the general population, rather than in special circumstances or high-risk subgroups. Examples of these are discussed in Chapters 61–63. In all cases, the design and implementation of preventive measures require translational research to ensure safety, optimize feasibility and impact, and critically evaluate all stages of the process.
Cancer Prevention and Control
A growing number of population-level preventive interventions are proving to be highly effective, as confirmed by the decreases in incidence as well as mortality rates from certain cancers (Chapters 61–63). Tobacco control has reduced the age-standardized incidence rate of lung cancer by up to 40% among men in high- and middle-income countries. Increased screening for colorectal cancer and removal of precursor lesions is credited for the 30% decrease in the incidence rates at this site in the United States. Universal neonatal vaccination against hepatitis B virus (HBV) has markedly decreased the prevalence of chronic HBV infection and liver cancer at younger ages in high-risk areas of East Asia and will yield maximal benefits against cancer in the future. The development of safe and effective vaccines against human papillomavirus (HPV) and less expensive and less onerous screening tests for cervical cancer have greatly expanded opportunities to prevent HPV-related cancers among women in many LMICs. Increased funding is becoming available for application research and cancer preventive services in LMICs. Cancer prevention presents both opportunities and challenges, as discussed in Part V of the text. The best practices developed for tobacco control provide an encouraging model of how health-related policies can address the behavioral causes of cancer. However, these must be tailored to fit the particular social, economic, and other considerations that affect the exposure (Chapter 61).
Advances in Genomics and other OMICs
Technological advances in high-throughput genotyping/sequencing and gene expression arrays have transformed research on both inherited (germline) susceptibility variants and the largely acquired (somatic) mutations in tumor tissue. Epidemiologic studies of cancer genetics have focused mainly on germline variants associated with cancer risk and etiology, whereas clinical and basic researchers have characterized the landscape of somatic alterations in tumor cells that drive the development and progression of cancer.
Germline Susceptibility Variants
The tools to identify inherited genetic susceptibility variants have advanced enormously since publication of the previous edition of this text in 2006. At that time, studies involved either high-risk families or the evaluation of a small number of pre-specified “candidate genes” in case-control studies of sporadic cancers in the general population. The candidate gene approach was largely unsuccessful in identifying robust associations for several reasons, including small sample size, limited statistical power, failure to account for multiple testing (generating negative and false positive results, respectively), and limited biologic knowledge to inform the selection of candidate genes. Following the completion of the Human Genome Project in 2003, genome-wide maps of single nucleotide polymorphisms (SNPs) became available. Advances in high-throughput genotyping technology, combined with knowledge about the structure of genetic linkage disequilibrium, created opportunities to conduct exploratory (hypotheis-free or “agnostic”) surveys across the entire genome. Over the past decade, GWAS have robustly identified more than 700 common (i.e., minor allele frequency >5%) susceptibility loci associated with cancer risk, as discussed for specific sites in Part IV, “Cancers by Tissue of Origin.” Because GWAS test millions of alleles across the genome, they require stringent criteria
(“genome-wide significance”), large sample size, and replication in more than one study to exclude chance associations. Most of the associations identified through GWAS are modest (per allele ORs: 1.5–2.0) or weak (ORs <1.5), but in aggregate these loci can distinguish a wide range of risk in the population, thus providing opportunities for targeted screening and prevention. While our current knowledge regarding germline risk comes from studies in populations of European ancestry, the identification of population-specific risk loci highlights the importance of conducting GWAS in diverse racial and ethnic populations.
Statistical modeling suggests that, for many cancers, additional variants remain to be identified, yet the search for variants with smaller effect sizes, as well as less common variants, drives the need for even larger studies. With the recent development of next-generation sequence technology, it is now practical to sequence whole exomes (coding regions plus regulatory regions) and whole genomes in population- and family-based studies in the search for heritability not identified through common variation in GWAS.
An important limitation of GWAS is biological interpretation, as the vast majority of risk variants revealed through GWAS are in non-coding genetic sequences. Functional analyses are underway to address this issue. The process is time-consuming, however, since it incorporates new bioinformatics tools and a comparison of gene expression in tumor and normal tissue to localize the functional SNP and ultimately the affected gene.
There has as yet been little progress in identifying interactions between inherited germline loci identified through GWAS and acquired “environmental” risk factors. Candidate gene studies have documented gene–environment interactions between tobacco smoking and the slow NAT-2 acetylation phenotype for bladder cancer (Chapter 52) and between alcohol consumption and slow ADH1B metabolizers for esophageal cancer (Chapter 30). However, much larger GWAS with more precise measures of exposure and risk will be needed to assess other, subtler gene–environment interactions.
Somatic Genomic Alterations
Most of the somatic genomic alterations, including mutations, indels, copy number alterations, and chromosomal rearrangements, that drive neoplastic progression in tumor tissue are acquired rather than inherited. As mentioned, the Human Cancer Genome Project and other international laboratory and clinical collaborations have characterized so-called driver mutations (i.e., those which confer growth advantage to a mutated cell line) for multiple types of human cancer (Chapter 4). These mutations represent the events involved in the multistage development of particular forms of cancer (Armitage and Doll, 2004; Hornsby et al., 2007; Wu et al., 2016). It is noteworthy that discoveries in somatic mutations over the past three decades provide strong support for the theory of multistage carcinogenesis that was proposed by Armitage and Doll, 10 years before elucidation of the structure of DNA, and over 30 years before the identification of the first proto-oncogenes and tumor suppression genes (Armitage and Doll, 1954). Sequencing studies have also implicated epigenetic modification as a major source of alterations in cancer (Chapters 2 and 4).
Variable combinations of genetic and epigenetic abnormalities account for the phenotypic heterogeneity within and among cancers. Molecular characterization of tumors is increasingly used to predict prognosis and to guide the use of targeted therapies for individual cancer patients. These markers are only beginning to be evaluated and integrated into large-scale epidemiologic studies, yet they are already changing the taxonomy of some types of cancers and are likely to profoundly affect future etiologic studies (Chapter 3). There has been some progress in efforts to link specific classes of somatic mutations, such as the mutational signatures of ultraviolet (UV) radiation, tobacco smoke, and oncogenic viruses, to established carcinogenic exposures (Chapters 2 and 4). These molecular signatures may, in the future, identify the causal exposure(s) for cancer in individuals as well as populations. Hopefully this goal will motivate interdisciplinary collaborations between epidemiologists, cancer prevention scientists, geneticists, cancer biologists, and clinicians.
Other OMICs
While genomic research is the poster child for the value of agnostic, comprehensive explorations of germline variants associated with cancer, other areas of OMIC research are moving toward this goal (Chapter 6). The development of technologies to screen many thousands of analytes related to gene expression (e.g., RNAseq), epigenetics (methylation; ChIP-Seq), metabolomics, and the microbiome will open new opportunities to identify the connections between exposures and the biologic effects that mediate carcinogenesis. Various OMIC technologies are at different stages of development. One of the more advanced efforts along these lines is the identification of hormone metabolites that influence breast cancer risk, illustrating the potential of these new technologies (Chapter 22).
OUTCOMES AND EXPOSURES
Changing Taxonomy of Cancer
Accurate and reproducible classification of neoplastic diseases is essential for advances in diagnosis and treatment, for quantifying geographic, temporal, and demographic variations in incidence, and for identifying etiologic relationships and mechanisms. Tumor classification has historically been based on the primary anatomic site and morphology for most solid tumors and on histologic characteristics for leukemias. Classification systems have evolved to incorporate information on morphology, genetics, cell lineage, developmental characteristics, and an array of molecular, clinical, and etiologic factors (ICD-O-3, 2013) (Fritz et al., 2000). While the refinement of cancer endpoints based on molecular or other characteristics will potentially increase the ability of etiologic studies to detect associations with specific tumor subtypes, it also poses serious challenges. Very large studies will be needed for both discovery and replication. Even well-established tumor markers are not measured uniformly in all patients. Newer classification systems based on molecular features have generally been evaluated in only a few hundred sporadic cancers, with little consideration of patient or population characteristics. Clonal heterogeneity within tumors and changes in tumor pathology during treatment further complicate classification (Norum et al., 2014). While the use of automated algorithms and computer-based image analysis is increasing among pathologists, these methods and the assessment of reproducibility and validity may not be reported to clinicians, epidemiologists, and others using the data. Population-based cancer registries are already challenged by efforts to keep abreast of changing tumor classifications, especially when the new criteria are not uniformly applied in a standardized manner.
Exposures and Exposure Measurement
More than 100 different agents and exposures are now designated as causally related to cancer in humans (Group I) by the International Agency for Research on Cancer (IARC). Variations in the prevalence and intensity of these exposures account for the striking geographic and temporal variations in the occurrence of many types of cancer. While many exposures such as tobacco, alcohol, and numerous industrial chemicals have long been classified as human carcinogens, exposure patterns change, new agents are introduced, the ability to measure exposures or outcomes progresses, and the quality, quantity, and/or specificity of evidence improves. For example, the contining global increase in obesity, metabolic syndrome, and type II diabetes, combined with improvements in laboratory assays to measure hormones in large population studies, has created new opportunities to study metabolic and hormonal effects on cancer. Thus, the discussion of “Hormones and Cancer” (Chapter 22) has been expanded to consider endogenous as well as exogenous exposures and peptide hormones (insulin, insulin-like growth factors, growth hormone, leptin, adiponectin, resistin, ghrelin, etc.) in addition to steroidal sex hormones. Several agents recently classified as Group 1 human carcinogens affect massive numbers of people. These include outdoor air pollution
(Chapter 17), the combustion of coal as household fuel (Chapters 16, 17, and 28), diesel engine exhaust (Chapter 17), the consumption of red and processed meat (Chapter 19), and to a lesser extent, UVemitting tanning beds (Chapter 14). The search for other modifiable causes of cancer continues. New associations have been reported with shift work, sedentary behavior (as distinct from physical inactivity), computed tomography scans during childhood, sun-sensitizing pharmaceutical drugs, and others. While the studies may be methodologically strong, the evidence for causality is not yet considered definitive. There is a continuing need to monitor both the immediate and longterm effects of more recently implemented medical technologies and newly developed drugs, products such as cellular phones and ecigarettes, nuclear accidents, exposures occurring in war zones, and other exposures potentially related to cancer.
Technological advancements in biomarker studies will allow more comprehensive examination of an individual’s metabolome, microbiome, genome, epigenome, and exposome. The use of specific biomarkers to assess internal exposures and identify children, adolescents, and other subsets of individuals who may be particularly susceptible to the factor being investigated (for example, dietary exposure, pesticide acting as a hormonal disruptor, or medication) could increase our ability to detect complex exposure–disease relationships.
ESTIMATES OF ATTRIBUTABLE FRACTION
Epidemiologists have long debated the fraction of cancer cases or deaths that could be avoided by preventive interventions (Chapter 61). Estimates of the percent of cancer deaths that could theoretically be avoided, if the exposures were eliminated, range from 50% to 80%, although the potential for primary prevention differs for incidence and mortality, by geographic region, gender, and attained age (Whiteman and Wilson, 2016). About half of the deaths that could be avoided in principle relate to 11 potentially avoidable risk factors, including the behavioral risk factors discussed above. The attributable fraction estimates are predicated on the idea that cancer risk is largely acquired, rather than inherited. Inherited factors do contribute to the variation in risk among individuals, but they cannot account for the large temporal changes in risk within countries, or the differences in risk among migrants who move from one country to another.
Chapter 19, “Diet and Nutrition,” provides the first estimates of the fraction of all cancers attributable to diet, in combination with or separate from overweight and physical inactivity. The authors estimated the total as about 20% overall, which is weaker than previously estimated. The proportion contributed by dietary composition independent of adiposity is less clear because some dietary factors have yet to be identified or established with sufficient certainty, and associations are likely underestimated because of measurement error or misspecification of temporal relationships. The authors estimate an etiologic contribution of 5%–12% for dietary composition alone, but suggest that this could be appreciably higher when considering nutrient and genetic interactions.
ONGOING CHALLENGES
Tumor Diagnosis and Classification
In LMICs, the completeness and specificity of tumor diagnosis varies depending on economic resources and medical infrastructure. Less than 10% of people in Africa and South America are covered by population-based tumor registries (Chapter 8). In high-income countries, tumor classification is more advanced because of earlier application of diagnostic innovations and revised classification systems. Classification systems evolve with the introduction of new histochemical and molecular markers and advances in understanding tumor biology. Even in high-income countries, there is wide variability in the proportion of tumors incompletely or inadequately characterized. Molecular profiling at major cancer centers may include a range of established tumor markers, exome or whole genome sequencing, copy
number, messenger and micro RNA sequencing, DNA methylation, and proteomics analysis (Hoadley et al., 2014). While this information may be useful clinically, it is not yet available for most cancer patients, nor are the data routinely incorporated into cancer surveillance systems (Chapter 8). Even cancers that have undergone intensive multidisciplinary review to improve classification, such as hematopoietic and lymphoproliferative malignancies, include subtypes characterized as “not otherwise specified” or provisionally classified (Swerdlow et al., 2016). Thus epidemiologic studies of cancer must collect and archive tumor tissue in order to ensure a uniform, more complete, and contemporary approach to molecular testing.
Over-diagnosis
“Over-diagnosis” refers to the incidental detection of small and/or indolent cancers that otherwise might not cause clinical problems during the patient’s lifetime (Chapter 8). Extreme examples of this have been the sudden increase in prostate cancer diagnoses following the introduction of PSA screening (Chapter 53), and the increase in thyroid cancer diagnoses due to screening programs using ultrasound (Chapter 44). Overdiagnosis is most problematic if it leads to unnecessary treatment and serious adverse effects. The introduction of new screening tests can also distort temporal trends in incidence and bias observational studies of the impact of screening (Chapter 63). The likelihood of over-diagnosis varies by cancer site and depends on the baseline incidence and risk characteristics of a population. An estimated 10–30% of newly diagnosed breast cancers identified with screening mammography may reflect over-diagnosis (Bleyer & Welch, 2012; Loeb et al., 2014; Vickers et al., 2014). In the absence of molecular markers that reliably distinguish indolent from aggressive tumors, clinicians must grapple with the potential for “over-treatment” (Chapter 3). Over-diagnosis poses a greater clinical dilemma for early stage cancers in internal organs than for premalignant lesions detected by colorectal or cervical screening, because the treatment is more invasive.
Exposure Measurement Issues
Regardless of the epidemiologic study design used, it is challenging to characterize accurately many types of acquired exposures due to a lack of comprehensive measurements during the relevant exposure window. This presents a greater problem for some exposures than others. For example, as described in Chapters 19–21, misclassification of exposure is of great concern in characterizing patterns of nutrition and physical activity, especially at earlier stages of life. It presents less of a problem in studying cigarette smoking, menopausal hormonal therapy, or exposure to microbial agents, since these exposures can be reasonably well defined qualitatively, and biomarkers exist to supplement questionnaire data. Certain exposures are experienced in multiple settings, including workplace, residential, recreational, medical, war zone, and other settings. Chemical exposures often occur as mixtures in air or water. Surrogate measures, such as job titles for occupational exposures and administrative databases for residential exposures, do not capture variations among individuals or over time.
The timing of exposure is an area of special interest and challenge. Exposures that occur during a particular time window or a susceptible stage of development may have adverse effects that are not evident when exposure occurs later in life. A classic example of this involved in utero exposure to high doses of the hormone di-ethyl stilbesterol (DES) in the daughters of mothers treated to prevent pregnancy complications, who subsequently developed vaginal carcinoma in adolescence (Chapter 49). For breast cancer, it is hypothesized that hormonal exposures received in utero or immediately postnatally may affect early stages in tumor development, or that breast tissue may be more susceptible to certain exposures (e.g., ionizing radiation, cigarette smoking, or alcohol consumption) during the period between menarche and first full-term pregnancy, when cells are proliferating but not fully differentiated (Chapter 45). Similar hypotheses have been proposed for nasopharyngeal cancer and Hodgkin lymphoma in relation
to early childhood infection with Epstein-Barr virus (Chapters 26 and 39). Although these hypotheses are important, they are difficult to test without biomarkers or experiments of nature that demarcate the timing of exposure. Serial acquisition of biological samples over many years of follow-up would be informative, although this approach must be tempered by feasibility and cost considerations.
FUTURE RESEARCH DIRECTIONS
While individual chapters outline future research directions for specific exposures or cancers, we highlight here selected cross-cutting issues that apply broadly to many cancers.
Team Science
One of the benefits of GWAS and pooled risk factor studies has been the formation of multi-institutional international consortia to share biospecimens and primary data in order to maximize statistical power for discovery and robust replication (Boffetta et al., 2007). These consortia have been instrumental in creating new models of funding, leadership, and authorship, and in sharing and harmonizing primary data across studies. The formation of larger and more complex data sets has stimulated innovations in informatics and the development and application of novel analytic methods. Further advances in high-throughput laboratory technology will continue to create new opportunities to explore the complex biology of genomics, metabolomics, proteomics, and so on, in large population studies. This will generate vast amounts of data to be analyzed. It will also require insights from diverse disciplines to plan analyses and to interpret the results.
“Transdisciplinary research” signifies a level of collaboration in which researchers from different scientific disciplines come together to identify the most important research questions, design the optimal approach, and collect, analyze, and publish the study results jointly (Rosenfield, 1992). This level of team science transcends disciplinary boundaries and benefits all parties. For example, the application of haplotype analyses based on the structure of genetic linkage disequilibrium, initially proposed by geneticists, greatly accelerated exploratory analyses across the entire genome in large population studies. Similarly, the involvement of epidemiologists in tumor genomics has brought a population science perspective to this field, increasing attention to population sampling, sex, and racial/ethnic differences, and exposures such as smoking that can affect the mutational spectrum of various cancers. There are many opportunities for collaborations involving laboratory scientists, analytic chemists, epidemiologists, and others to accelerate research on etiologic issues related to cancer. One example would be transdisciplinary research to understand hormonal carcinogenesis at the molecular level in human populations (Chapter 22).
Cancer Survivorship
The number of people surviving after a diagnosis of cancer has increased rapidly in high-income and many middle-income countries due to improvements in treatment and the effects of screening on both early diagnosis and more complete ascertainment. In the United States, the estimated number of people alive for at least 5 years after a diagnosis of cancer increased from 4 million in 1978 (~1.8% of the population) to 13.7 million in 2012 (~4% of the population), and is predicted to approach 18 million by 2022 (de Moor et al., 2013; Harrop et al., 2011). A substantial proportion of these are long-term survivors. Forty percent of individuals who survived for at least 5 years were alive 10 or more years after diagnosis, and 15% had survived 20 or more years (Howlader et al., 2015). To address the rapidly increasing population of cancer survivors, the NCI Office of Cancer Survivorship and a 2006 publication from the Institute of Medicine (Committee on Cancer Survivorship, 2006) provided a framework for identifying and addressing the unmet needs of this growing population. Disease and treatment affect multiple health domains (e.g., medical, physical
function, psychiatric and psychosocial, cognitive, work, sexual, and reproductive). These factors and heath-related quality of life should be assessed at discrete intervals following diagnosis. Studies should examine whether quality of life and survivorship issues differ for cancers in children from those in later life. Research on survivorship is largely still in its infancy (de Moor et al., 2013; Harrop et al., 2011; Richardson et al., 2011). The occurrence of multiple primary and secondary cancers following treatment is an important area of research (Chapter 60). Cancer epidemiologists should have a major research role in cancer survivorship because of their expertise in observational study designs and exposure assessment.
Risk Prediction Models
Risk prediction models estimate the absolute risk of being diagnosed with or dying from a specific condition during a defined time period for individuals with defined demographic characteristics and risk factors. These models are widely used to predict individual risk and to guide treatment decisions in cardiovascular medicine. Unfortunately, the models currently available for cancer provide reasonably accurate predictions for groups of people but not for individuals (Amir et al., 2010).
Site-specific chapters discuss research on risk prediction models for cancers of the lung (Chapter 28), colorectum (Chapter 36), breast (Chapter 45), and multiple primary cancers (Chapter 60). Brinton and colleagues in Chapter 45 review the research on factors that may improve the discriminatory accuracy of existing models of breast cancer. These include endogenous hormone levels, proliferative benign biopsy diagnoses, behavioral risk factors, mammographic density, and genetic polymorphisms. Although the associations with genetic polymorphisms identified by GWAS are modest (per allele ORs: 1.5–2.0) or weak (ORs <1.5), as discussed earlier, it is hoped that in the aggregate the addition of these loci to the model can more accurately predict risk for individuals, thereby improving targeted approaches for screening and prophylactic treatment (Garcia-Closas et al., 2014).
Risk prediction models of colorectal cancer have been used to estimate the independent and combined effects of behavioral, medical, familial and genetic risk factors on attributable risks. One such study estimated that a population with the optimal distribution of established modifiable risk factors for colorectal cancer would have a 43% percent lower (95% CI: 0.14, 0.65) incidence of disease (Lee et al., 2016). Meester et al. (2015) estimated the effect of screening on deaths from colorectal cancer and concluded that the non-use of screening methods among people aged ≥ 50 years in the United States accounted for more than 50% of colorectal cancer deaths.
The Microbiome
Remarkable advances have been achieved in identifying microbial pathogens that influence cancer risk (Chapter 24). This research has focused historically on disease-causing organisms, rather than on the trillions of “commensal” organisms that live in or on the human body. Increased interest in the human microbiome has broadened the scope of inquiry. The greatest concentration of commensal microorganisms is in the upper and lower gastrointestinal tract, although there are well-characterized symbiotic communities in the skin, mouth, sinonasal cavities, and vagina. Diverse species of bacteria, archaea, viruses (including bacteriophages), and fungi can be identified. Some species have coevolved with humans for millennia and maintain essential physiologic enzymatic functions, such as the synthesis of essential vitamins and the metabolism of carbohydrates, bile acids, and xenobiotics. Commensal flora may have detrimental as well as beneficial effects on cancer. The colonic microbiome is thought to account for the approximately 40-fold higher incidence of adenocarcinoma in the colon than in the small intestine (Chapter 35). While the small intestine is not sterile, it has comparatively few commensal organisms. The difference in cancer risk between the two sites is remarkable, given that both organs undergo rapid cell replication. The small intestine comprises about 90% of the mucosal absorptive surface area of the
gastrointestinal system, yet in the United States accounts for only 3.2% of digestive system cancer cases (Howlader et al., 2015).
The tools for studying complex microbial communities are only now becoming available. There is great interest, however, in characterizing alterations in the microbiome caused by changes in diet, antibiotic use, and other exposures, and in the inflammatory responses that result from the influx of pathogenic organisms into organ-specific microbiomes (Dale and Moran, 2006). Future epidemiologic and experimental research on the human microbiome will likely continue to focus on the carcinogenic effects of disturbed homeostasis and the disruption of the normal diversity of the microbial flora (Bultman, 2016), and as well as on potential role(s) of the microbiome on the pathogenesis of obesity, diabetes (Okeke et al., 2014), and autoimmune diseases (Hooper et al., 2012).
Development of New Cohorts
There is an ongoing need to develop new cohorts to complement existing cohorts, with a particular focus on collecting and banking biological samples needed for broader OMICs studies (e.g., tumor tissue, blood, urine, stool), the inclusion of state-of-the-art exposure measurements and data collection strategies, data on new and emerging exposures, and repeated assessments over time to capture important changes in exposures, behaviors, or physiological factors. Besides enrolling participants from more recent birth cohorts, there is also a critical need to increase the racial/ethnic and socioeconomic diversity of participants. Careful consideration must be given to cost-effective data sources and methods of data collection to address these needs in the long-term follow-up of future cohorts. Data access and data sharing also need to be considered since data collected from more recent cohorts (such as the UK Biobank, the NCI Cohort Consortium, and the Childhood Cancer Survivor Study) are increasingly made broadly available as a resource for qualified investigators. Finally, new models of governance and participant engagement and interaction will need to be developed for the next generation of cohort studies.
New and Non-Traditional Data Sources
A variety of new data sources are enriching the opportunities for descriptive and analytic epidemiologic studies. The expanding use of electronic health records, along with a movement toward interoperability and standardized content, can potentially provide individual-level medical data on tumor characteristics, comorbidity, and treatment. Data linkage between population-based cancer registries, vital status and mortality records, hospital and other medical records, and administrative data sets provides an important resource for studies of cancer survivorship. Personal devices such as accelerometers or smart phones to track movement can improve the measurement of physical activity.
In parallel, many other types of digital data are increasingly available. Potentially linkable data from diverse fields of science (e.g., OMICs; environmental and geographic sciences) and areas outside of science (e.g., business, finance, telecommunications, social media, and the Internet of things) are being promoted under the umbrella of “Big Data.” Non-traditional data sources have been touted as a revolutionary development in the future of epidemiology (Khoury and Ioannidis, 2014; Mooney et al., 2015). It should be recognized that the use of non-traditional data sources involves much more than working with large volumes of data. These sources have been characterized as high variety (secondary use from many diverse sources), high volume (both in numbers of observations and/or variables per observation) and high velocity (real time) (Douglas, 2012). It is important that epidemiologists collaborate with informaticians and computer scientists to explore the promise of Big Data. Expertise in observational study design, along with efforts to assess validity and reproducibility, will be essential to avoid “big error” driven by chance, bias (e.g., selection bias, measurement error, confounding) and lack of external validity. Cancer epidemiologists bring the subject matter expertise needed to frame and interpret Big Data results for clinical and public health relevance. While the long-term impact of Big Data on cancer surveillance
