10 Review of American College of Rheumatology (ACR) Convergence 2024, November 14–19, 2024
Congress Features
19 Rheumatology’s Most Impactful Discoveries This Year
Katrina Thornber
24 Harnessing the Power of AI in Rheumatology Without Getting Burned
Victoria Antoniou
Abstract Reviews
28 Management Practices for Raynaud’s Phenomenon in Patients with Systemic Sclerosis: Real-World Data from Community-Based Practices in the United States
Ozen et al.
31 Machine Learning-Based Risk Stratification Tool to Predict Early Flare for Rheumatic and Musculoskeletal Diseases
Moon et al.
33 Effect of a Whole Food Plant-Based Diet in Patients with Gout: A Pilot Randomized Controlled Trial
Kretova et al.
36 Improving Prior Authorization Efficiency with Artificial Intelligence: A Study on Rheumatology Investigations and Treatments
Badsha et al.
39 A Qualitative Exploration of Oral Healthcare Needs Amongst Canadian Patients with Rheumatic Diseases and Their Providers
Stavropoulou et al.
40 VIVA QI – Vaccination In Vasculitis: Applying a Quality Improvement Approach
Mah et al. Interviews
43 John H Stone
47 Roy Fleischmann
51 Daniel Wallace Feature
53 Current Applications and Future Roles of AI in Rheumatology
Chan Article
59 Steroid-Induced Hyperglycemia in Rheumatoid Arthritis: A Case Report
Shreen et al.
"At its heart, the Convergence embodied the ACR’s mission: to empower rheumatology professionals to excel in their practice..."
Editorial Board
Ayşen Akinci
Hacettepe University, Ankara, Türkiye
Elena Myasoedova
Mayo Clinic Rochester, Minnesota, USA
Arthur Kavanagh
University of California San Diego, California, USA
Ian C. Chikanza
The Royal London Hospital, UK
Isabelle Amigues
UnabridgedMD, Denver, Colorado, USA
Yoshiya Tonaka
University of Occupational and Environmental Health, Japan
Judith A. Smith
University of Wisconsin School of Medicine and Public Health, Madison, USA
Christine Peoples
University of Pittsburgh Medical Center, Pennsylvania, USA
Aims and Scope
AMJ Rheumatology is an open access, peer-reviewed ejournal committed to helping elevate the quality of practices in rheumatology globally by informing healthcare professionals on the latest research in the field.
The journal is published annually, 6 weeks after the American College of Rheumatology (ACR) Convergence, and features highlights from this event, alongside interviews with experts in the field, reviews of abstracts presented at ACR 2024, as well as in-depth features on sessions from this event. The journal also covers advances within the clinical and pharmaceutical arenas by publishing sponsored content from congress symposia, which is of high educational value for healthcare professionals. This undergoes rigorous quality control checks by independent experts and the inhouse editorial team.
AMJ Rheumatology also publishes peer-reviewed research papers, review articles, and case reports in the field. In addition, the journal welcomes the submission of features and opinion pieces intended to create a discussion around key topics in the field and broaden readers’ professional interests. The journal is managed by a dedicated editorial team that adheres to a rigorous double-blind peer-review process, maintains high standards of copy editing, and ensures timely publication.
AMJ Rheumatology endeavours to increase knowledge, stimulate discussion, and contribute to a better understanding of practices in the field. Our focus is on research that is relevant to all healthcare professionals in this area. We do not publish veterinary science papers or laboratory studies not linked to patient outcomes. We have a particular interest in topical studies that advance knowledge and inform of coming trends affecting clinical practice in rheumatology.
Further details on coverage can be found here: www.emjreviews.com/en-us/amj/.
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AMJ is supported by various levels of expertise:
• Guidance from an Editorial Board consisting of leading authorities from a wide variety of disciplines.
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This Publication
Launch Date: December 24, 2024
Frequency: Annually Online ISSN: 2977-5868
All information obtained by AMJ and each of the contributions from various sources is as current and accurate as possible. However, due to human or mechanical errors, AMJ and the contributors cannot guarantee the accuracy, adequacy, or completeness of any information, and cannot be held responsible for any errors or omissions. AMJ is completely independent of the review event (ACR 2024) and the use of the organisations does not constitute endorsement or media partnership in any form whatsoever. The cover photo is of Washington, D.C., the location of ACR 2024.
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Welcome
Dear Readers,
Welcome to the inaugural issue of AMJ Rheumatology, the first of its kind and the final publication of AMJ this year. This issue is a celebration of the inspiring advances amplifying the quality of healthcare in clinical rheumatology. In the current era of generative AI, we share expert cutting-edge research on the limitations and leverage of AI, and invite you to share your opinions on its role in revolutionizing rheumatology. You will also find interviews with notable figures across the specialty, illuminating their indispensable roles and how they impact patient outcomes, covering “eureka moments” in IgG4-related disease and the highly sophisticated, and expensive, CAR-T cell therapy.
Washington, D.C., was where healthcare providers, researchers and trainees, industry professionals, advocates, and policymakers congregated to examine the latest research developments and breakthroughs at the 6-day American College of Rheumatology (ACR) Convergence 2024. The society continues to invest in education and research to advance the field of rheumatology, which was made evident at the stimulating and ambient meeting with its non-stop schedule and lively atmosphere.
As we look back on a fantastic year in this dynamic field, I am proud to reflect on our journey here at AMJ. I would like to thank our Editorial Board who are starting on this new journey with us, contributors, and dedicated editorial team.
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Foreword
Dear Readers,
Welcome to the first issue of AMJ Rheumatology, which features highlights from the Annual American College of Rheumatology (ACR) Convergence, held from November 14th–29th, 2024, in Washington, D.C.
The event saw experts from around the globe come together to present cutting-edge research findings and key updates across a variety of disciplines within rheumatology. The opening plenary, led by Deborah Dyett Desir, Yale School of Medicine, New Haven, Connecticut, included an assessment of the priorities of the ACR in collaboration with other key societies to cultivate an inclusive environment for this diverse and dynamic field. The event is a chance to celebrate the global rheumatology community together as we serve and collaborate with an international workforce.
This issue of AMJ Rheumatology contains features on key sessions at congress, including the year in review, in which Michael H. Pillinger, NYU Langone Medical Center, New York, exclaimed that we are embarking on an “extraordinary therapeutic adventure”, with many more remarkable developments to be expected in the coming years.
Additionally, we feature a range of abstracts presented at the ACR Convergence 2024, and interviews with John H. Stone, Massachusetts General Hospital, Boston; Roy Fleischmann, University of Texas Southwestern Medical Center, Dallas; and Daniel Wallace, Cedars-Sinai Medical Center, Los Angeles, California. You will also find a fascinating case of hyperglycemia in rheumatoid arthritis and a topical feature on current applications and future roles of AI.
We hope you enjoy this celebratory publication showcasing the successes and frontiers of knowledge in this vibrant community
I would like to thank all authors, peer reviewers, and Editorial Board members who contributed to the success of this issue's efforts to elevate the quality of clinical practice worldwide.
We hope you enjoy this celebratory publication showcasing the successes and frontiers of knowledge in this vibrant community, and look forward to the ACR Convergence 2025 in Chicago, Illinois.
Elena Myasoedova Mayo Clinic,
Rochester, Minnesota, USA
ACR 2024
At its heart, the Convergence embodied the ACR’s mission: to empower rheumatology professionals to excel in their practice...
Review of the American College of Rheumatology (ACR) Convergence
SET against the vibrant backdrop of Washington, D.C., this year’s American College of Rheumatology (ACR) Convergence was truly unforgettable. Bringing together the brightest minds in rheumatology, the congress showcased a wealth of knowledge through scientific sessions, abstract presentations, symposia, and an impressive array of scientific posters. Experts from across the globe shared the latest breakthroughs, sparking conversations that are shaping the future of the field.
At its heart, the Convergence embodied the ACR’s mission: to empower rheumatology professionals to excel in their practice, advance the specialty, and inspire progress. As the leading authority and trusted partner for rheumatology professionals, the ACR remains committed to supporting healthcare providers so they can deliver the best care to their patients.
The 2024 ACR Convergence emphasized innovation, collaboration, and cutting-edge research, creating a dynamic platform to drive advancements in rheumatology.
The bustling event kicked off with a welcome from the 87th ACR president, Deborah Dyett Desir, Yale School of Medicine, Woodbridge, Connecticut, who expressed her gratitude towards the attendees of this year's congress for gathering for the convergence in the nation’s capital, Washington, D.C.
“ACR Convergence is brought to you by the phenomenal work of our staff and the talented
and dedicated ACR and Association of Rheumatology professionals and volunteers. It is through their hard work and dedication that we can make this the premier event of the year for physicians, researchers, advanced practice practitioners, pharmacists, physical and occupational therapists, practice managers, and other medical professionals,” Desir highlighted to the gathered attendees. The aim of the ACR Convergence 2024 was to celebrate the remarkable achievements of the ACR and to commemorate 90 years of forward momentum by honoring the legacy and ensuring the future.
The aim of the ACR Convergence 2024 was to celebrate the remarkable achievements of the ACR and to commemorate 90 years of forward momentum by honoring the legacy and ensuring the future
The ceremony continued with Desir sharing the many ways through which the Convergence aims to uphold its mission and fulfill its brand promise. Desir explained that ACR fulfills its promise through its relentless advocacy efforts at Capitol Hill and State Houses across the country. This includes initiatives such as the advocacy leadership conference at Capitol Hill Day, where ACR ensures that the voices of rheumatology professionals are heard and their needs are prioritized in policy discussions, as well as active campaigning for better legislation that will have a positive impact on healthcare professionals and patients alike. Another effort to support healthcare professionals was the establishment of the "Women in Rheumatology Task Force". "With over half of medical school graduates and 66% of ACR fellows being women, it is essential to create an environment where women feel truly at home, where their unique
needs are prioritized," Desir said. She created the task force this year for women in rheumatology with the aim of fostering the growth and success of women in the field. The task force will provide strategic recommendations for developing and expanding resources, programs, and advocacy efforts that promote leadership and professional development for women in rheumatology, with a focus on key areas such as career advancement, working in mentorship opportunities, pay equity, and family support policies. The task force will collaborate with the Association of Women in Rheumatology (AWIR) in these efforts. By addressing critical issues such as worklife balance, access to mentorship, and leadership development, one can ensure that women have every opportunity to thrive and succeed.
Desir then introduced another notable initiative, the "Climate Change and
With over half of medical school graduates and 66% of ACR fellows being women, it is essential to create an environment where women feel truly at home, where their unique needs are prioritized
Rheumatology Task Force", as understanding the impact of climate change on health is important when it comes to providing the comprehensive care that patients deserve. As Desir explained, rheumatologists witness firsthand the effects of climate change, and how they worsen the conditions of patients with chronic rheumatic disease, making them more vulnerable to disease exacerbations triggered by worsening environmental factors. These impacts are felt most acutely by socio-economically disadvantaged populations who already face significant barriers in accessing effective treatment. “I recognize the urgency of this issue, and I empower the task force to investigate how climate change affects patients with rheumatic diseases and provide a strategic and proactive response,” announced Desir, with a further explanation that by addressing this challenge now, ACR places itself at the forefront of the issue that impacts patients.
Desir explained that ACR achieved its promise by embedding Diversity, Equity, Inclusion & Belonging (DEIB), into the very foundation of the organization. By emphasizing DEIB, ACR addresses the needs of all ACR members. This is a fundamental aspect of ACR’s vision; it is the need for greater diversity in rheumatology and within ACR leadership. ACR’s commitment to DEIB is not only about bringing the wealth of perspectives, experiences, decisionmaking, and innovation, but it is also about creating unobstructed pathways for underrepresented groups to leadership roles, stressed Desir, as this ensures that ACR will remain relevant and responsive to the diverse membership of the ACR and ARP. “Our leadership, membership, and the workforce should reflect the diversity of our patients, guaranteeing that our organization is truly representative of the communities we serve,” explained Desir.
Continuing, Desir addressed the rheumatology workforce shortage and how ACR plans to tackle this issue head-on. The efforts include expanding
recruitment strategies to attract more medical students and residents to the field of rheumatology with targeted outreach, educational programs, and scholarships. In an exciting announcement, Desir introduced "Rheumatology for Primary Care", a new digital resource designed to support primary care practitioners in diagnosing and referring both pediatric and adult patients with rheumatic diseases. In the closing remark, Desir reassured the attendees that ACR’s commitment to addressing the rheumatology workforce shortage remains steadfast, ensuring that patients across the country have access to the specialized care they need and deserve.
In a celebration of global engagement and outreach, Desir welcomed the international attendees to this year's event, where they can connect, share knowledge, and celebrate the global rheumatology community together. With 10,000 members across 98 countries, this global community forms the vibrant and essential core of the ACR.
10,000 members
98 countries
To conclude the opening ceremony, Desir urged the attendees to explore the many scientific sessions, peruse the poster hall, visit the exhibit hall, engage in networking lounges, and take advantage of meet-theprofessor sessions, late-breaking abstract sessions, and much more!
Read on for more key insights into ACR Convergence 2024, and make sure to join us next year for ACR Convergence 2025, which will take place in Chicago, Illinois.
Low-Dose Prednisone Reduces Relapse Risk in Granulomatosis with Polyangiitis
MAINTAINING low-dose prednisone therapy significantly reduces relapse risk in patients with granulomatosis with polyangiitis (GPA), according to recent research presented at the ACR Convergence 2024.
By Month 6
%
(11/71) of the 0 mg/day group relapsed, compared to just
%
(3/72) of the 5 mg/ day group
The Assessment of Prednisone in Remission (TAPIR) trial evaluated the efficacy and safety of 5 mg/day prednisone compared to complete discontinuation over 6 months, providing critical insights for clinical practice. The study enrolled 143 patients who were in remission following treatment for active GPA.
Participants, all receiving prednisone at 5–20 mg/day, tapered to 5 mg/day before being randomized to either continue this dose (72 patients) or discontinue prednisone entirely (71 patients). Other immunosuppressive therapies, such as rituximab, were maintained. The primary focus was relapse rates at 6 months, defined by a need to restart or increase glucocorticoid dosage.
Findings showed that patients on 5 mg/ day prednisone were significantly less likely to experience relapse than those who discontinued prednisone entirely. By Month 6, 15.5% (11/71) of the 0 mg/day group relapsed, compared to just 4.2% (3/72) of the 5 mg/ day group, with an odds ratio of 4.22 (95% CI: 1.1–15.8). The relapse risk difference was particularly stark among patients not on
rituximab, where the discontinuation group had a relapse rate of 20.0% versus 2.6% in the low-dose group (odds ratio: 9.50; P=0.023). Among rituximab users, relapse rates were comparable between groups (8.8% versus 6.1%; P=0.667).
Time to relapse was also significantly shorter in the discontinuation group (P=0.026), although most relapses (93%) were minor. Safety outcomes, including serious adverse events and infections, showed no significant differences between the groups, with six events in five patients on 0 mg and one event in the low-dose group (P=0.492). Patientreported outcomes, such as fatigue and physical function, were similarly unaffected.
This study shows the value of low-dose prednisone in preventing GPA relapses, particularly for patients on non-rituximab therapies. While the risk of major relapses remains low, these findings highlight the importance of tailored tapering strategies in GPA management and future clinical trial designs.
Urinary Biomarker Panel Offers Non-invasive Breakthrough for Lupus Nephritis
A STUDY presented at the ACR Convergence 2024 showed that urinary biomarker panels can transform the diagnosis and management of lupus nephritis (LN), providing a noninvasive and highly accurate alternative to traditional methods.
LN, a severe complication of systemic lupus erythematosus, often requires kidney biopsies to determine disease activity. However, traditional biomarkers such as C3, C4, and anti-dsDNA offer limited accuracy, making it difficult for clinicians to monitor disease progression and response to treatment. This study introduced a panel of 12 urinary proteins that can identify active proliferative LN, characterized by a National Institutes of Health (NIH) Activity Index >2, with remarkable precision.
The biomarker panel, developed using machine learning techniques, demonstrated an impressive area under the curve of 90%, significantly outperforming traditional markers like C3 (73%) and C4 (67%). Key proteins such as interferon-gamma receptor 1, CD163, and CEACAM-1 emerged as crucial indicators. Importantly, the panel not only predicted disease activity but also tracked treatment responses. Patients classified as complete responders after 1 year displayed noticeable improvements in biomarker
activity scores within the first 3 months, distinguishing them from partial or nonresponders.
The findings present the potential of this panel to replace invasive kidney biopsies, offering a targeted approach to understanding intrarenal inflammation. Unlike proteinuria, which reflects general kidney damage, these biomarkers provide specific insights into LN activity. By accurately predicting histological activity and monitoring treatment outcomes, the panel could enable more effective and personalized care for patients with LN.
This study introduced a panel of 12 urinary proteins that can identify active proliferative LN
With further validation, this urinary biomarker panel could become an essential tool for clinicians, revolutionizing the diagnosis and management of lupus nephritis.
Enhanced Fertility in Women with Rheumatoid Arthritis: A Treat-to-Target Approach
ACCORDING to new research presented at the ACR Convergence 2024, fertility is increased in women with rheumatoid arthritis (RA) when treated according to a treat-to-target strategy.
High rates of infertility and prolonged time to pregnancy (TTP) have both been observed in females diagnosed with RA. In a previous cohort study, known as the Pregnancyinduced Amelioration of RA cohort (PARA), RA-related factors shown to affect time to pregnancy were high disease activity, daily non-steroidal anti-inflammatory drug use, and daily prednisone intake exceeding 7.5 mg. Comparatively, the Preconception Counseling in Active RA (PreCARA) study followed women wishing to conceive with a treat-to-target treatment strategy and counseling, aimed at avoiding the use of non-steroidal anti-inflammatory drugs and high-dose prednisone. Radboud Dolhain and team, from the Erasmus University Medical
Center, Rotterdam, the Netherlands, set out to investigate whether a treat-to-target approach, including TNF-inhibitors, improved TTP pregnancy in the Pre-CARA cohort compared to the PARA cohort.
In both the PreCARA (n=215) and PARA (n=245), TTP was defined as the time between unprotected sexual intercourse and the onset of the last menstrual period, and differences in TTP were analyzed using Kaplan-Meier curves. The median disease activity was lower in the PreCARA cohort compared to PARA. Additionally, 3% of the patients in PreCARA did not take any medication in the preconception period compared to 36% in the PARA cohort. Notably, in the PreCARA study, the median TTP was 84 days in patients who got pregnant, in contrast to 196 days observed in the PARA study. TTP exceeded 12 months in 23% of PreCARA patients compared to 42% in the PARA patients. Additionally, fewer patients took daily doses of prednisone exceeding 7.5 mg in the PreCARA versus PARA cohort (23% versus 48%).
The median TTP was 84 days in patients who got pregnant, in contrast to 196 days observed in the PARA study
These results show that TTP was significantly shorter in the PreCARA patients than the PARA, highlighting the benefit of treat-totarget treatment strategies to improve TTP in women diagnosed with RA.
Reducing Racial and Ethnic Outcome Disparities in Juvenile Idiopathic Arthritis
RESEARCH presented at the ACR Convergence 2024 conference has demonstrated that reducing disparities in patients with juvenile idiopathic arthritis (JIA) is feasible at a large tertiary care center if certain strategies are implemented.
Pronounced racial and ethnic outcome disparities in the management of JIA have been reported, despite advances in novel therapeutics and treat-to-target interventions. At the Children's Hospital of Philadelphia, Pennsylvania, the mean population-level clinical Juvenile Arthritis Disease Activity Score (cJADAS) was 2.9, with greater values in nonHispanic Black (NHB) patients (5.0) compared to non-Hispanic White (NHW) patients (2.6). Therefore, researchers aimed to identify the key drivers of disparities, implement equityfocused interventions, and improve outcomes for patients. Specifically, the aim was to decrease the mean cJADAS from 2.9 to 2.7 in the full cohort and decrease by 1.2 units in NHB patients (50% of the baseline disparity gap) without widening the existing gap.
In early 2023, the research team identified the four drivers of racial and ethnic outcome disparities: consistent outcome documentation, application of JIA best practices, providing access to at-risk patients, and team awareness and agency. In a cohort of patients with a physician diagnosis of JIA seen within the prior 450 days, the researchers implemented strategies to reduce
outcome disparities, with monthly outreach to patients overdue for follow-up, standardization medication adherence assessments, monthly divisional cJADAS distribution, and quarterly data assessment workshops for maintenance of certification (MOC) credit.
By May 2024, the JIA population at the tertiary center had grown by 9.7%, consisting of 870 patients (68% NHW and 7% NHB). Additionally, the mean disease activity target attestation increased to 95%, exceeding the goal of 90%. After launching a medication adherence assessment, performance was stable at 75% of eligible visits.
After introducing all interventions by June 2023, the analysis revealed that the mean cJADAS decreased from 2.9 to 2.7. Specifically, in NHB patients, the mean cJADAS decreased from 5.0 to 4.4, and in the NHW patients from 2.6 to 2.4.
These findings demonstrate the ability to reduce racial and ethnic outcome disparities in JIA treatment if clinicians implement the right strategies. Refining such strategies and creating more targeted interventions will improve outcomes further.
Cancer Therapy Outcomes Similar for Patients with Autoimmune Diseases
IMMUNE checkpoint inhibitors (ICI) have transformed cancer treatment, providing hope for patients with a range of malignancies. However, a study presented at the ACR Convergence 2024 has highlighted that individuals with pre-existing autoimmune diseases are often excluded from clinical trials due to concerns about increased immune-related adverse events.
This exclusion has raised questions about whether such patients experience different treatment outcomes compared to those without autoimmune diseases, and this recent study has sought to address this gap by assessing mortality risk in a large national cohort of patients with autoimmune diseases undergoing ICI therapy.
Researchers utilized the TriNetX Diamond network, a comprehensive multi-center US database of electronic health records, to identify patients with and without preexisting autoimmune diseases receiving ICIs for cancers such as lung, digestive organ, melanoma, and urinary tract malignancies. Using the International Classification of Diseases, Tenth Revision codes, they analyzed mortality rates, adjusting for demographic and comorbid factors through propensity score matching, while survival outcomes were assessed using Kaplan-Meier analysis and Cox proportional hazards models.
The study included 25,153 patients with autoimmune diseases and 78,547 patients without autoimmune diseases. Initial analysis
showed slightly higher mortality rates in the autoimmune disease group at 40.0%, compared to the non-autoimmune disease group at 38.1% (hazard ratio: 1.07; 95% CI: 1.05–1.10). Notably, patients with autoimmune diseases exhibited significantly higher rates of cardiovascular comorbidities, such as Type 2 diabetes (42.0% versus 24.8%), chronic kidney disease (25.6% versus 15.5%), and ischemic heart disease (39.2% versus 28.4%).
After propensity score matching, which produced two balanced cohorts of 23,714 patients, no significant difference in mortality risk was observed as mortality rates were 39.8% in the autoimmune disease group and 40.2% in the non-autoimmune disease group (hazard ratio: 0.97; 95% CI: 0.94–1.00).
These findings suggest that patients with preexisting autoimmune diseases do not show an increased mortality risk when undergoing ICI therapy. This evidence challenges the prevailing rationale for excluding patients with autoimmune diseases from clinical trials, highlighting the potential for broader access to ICIs and emphasizing the need for inclusive trial designs.
Patients with autoimmune diseases exhibited significantly higher rates of cardiovascular comorbidities, such as
Rheumatology’s Most Impactful Discoveries This Year
EXPERTS at the American College of Rheumatology (ACR) Convergence 2024 identified and showcased the most groundbreaking discoveries in the field of rheumatology in the last 12 months in a session titled “Year in Review: Clinical Science”.
Tasked with presenting the key advances in clinical sciences for 2024, Michael Pillinger, New York University Grossman School of Medicine, New York, was introduced as someone known by the entire community as a master educator and recipient of numerous prestigious honors. As with all scientific presentations, Pillinger opened the session with his disclosures; however, he quickly set an engaging tone by stating that his real disclosure is that “there is just no way I could possibly present all of the great work that's transpired this year. So, I'm just going to start out with an apology for the other 99% of clinical research that I won't be including.”
RHEUMATOID ARTHRITIS
Taking the audience on a journey through a range of scientific advancements in rheumatological diseases, Pillinger began with rheumatoid arthritis (RA). He specifically drew attention to pre-RA and the ongoing goal to identify at-risk patients before disease onset: can RA be prevented by pre-clinical intervention? Several studies published this year have aimed to answer this question, albeit with “murky” results, explained Pillinger. He noted that finding the optimal treatment window and the optimal therapeutic agent is key.
A potential candidate that has been at the heart of several studies this year has been abatacept, a selective co-stimulation modulator with inhibitory activity on T lymphocytes. The APIPPRA trial, a Phase IIb clinical study, investigated the efficacy of abatacept in individuals at high
risk of developing RA.1 Participants received either 125 mg of subcutaneous abatacept weekly or a placebo for 12 months. At 24 months, 25% of participants in the abatacept group had progressed to RA, compared to 37% in the placebo group. Additionally, abatacept demonstrated improvements in pain, functional well-being, and quality-oflife measures, as well as reduced levels of subclinical synovitis.
Similarly, in the ARIAA trial, high-risk adults received weekly subcutaneous abatacept 125 mg or placebo for 6 months, followed by a drug-free, observation phase for 12 months.2 The results revealed that 6-month treatment with abatacept reduces inflammation, clinical symptoms, and the risk of developing RA in high-risk individuals. Notably, the benefits persisted throughout a 1-year drug-free observation phase.
Interestingly, Pillinger noted, a substantial number of patients receiving abatacept,
in both studies, immediately went on to develop RA. This can be looked at from two perspectives: either abatacept may have been effective in delaying the onset of RA, or it may have ultimately failed to prevent its development. However, by the end of both studies, particularly in the ARIAA trial, there was still a significant difference between the placebo and abatacept groups, and a meaningful number of patients who received abatacept never went on to develop RA.
GOUT
Pillinger transitioned from the most common autoimmune arthritis, RA, to the most common inflammatory arthritis in the US: gout. Drawing attention to the link between gout and cardiovascular (CV) risk, he emphasized the need for early CV risk management in these patients.
Patients with gout have about a two-fold increase in CV risk, including myocardial infarction (MI), compared to the general population. Generally, this increased risk has
been attributed to the chronic, long-standing impact of having an immune or inflammatory disease. However, a few years ago, it was observed that patients who experienced a gout flare had a significantly increased risk of MI and stroke for up to 120 days after the flare, indicating a pathological change that persisted after the flare.3 This year, the same research group reported the short-term risk of CV events in people newly diagnosed with gout.4 The results demonstrated that the incidence of cardiovascular events in the 30 days following a first gout diagnosis was significantly higher than in the subsequent 31–730 days after gout diagnosis. These findings support the need for attentive CV risk management in patients with gout, particularly within the first 30 days.
Patients with gout have about a two-fold increase in CV risk, including myocardial infarction (MI), compared to the general population
OSTEOARTHRITIS
Shifting now from the most common inflammatory arthritis to the most common arthritis overall, osteoarthritis (OA). Pillinger focused on knee OA, describing it as a condition that often makes clinicians “put our hands up to our heads and scream, because it's our most common disease, but we're so bad at managing it. We only treat the symptoms and send them to the surgeons.” However, there may be change on the horizon, as Pillinger highlighted a substantial number of clinical trials on knee OA that were published this year.
There have been a number of methotrexate studies over the last few years that suggest a possible benefit in OA. For example, the PROMOTE trial revealed that at 6 months, methotrexate was statistically superior to placebo in reducing knee pain.5 Other outcomes of function and stiffness were also significant compared to placebo at 6 months. However, there were some limitations in the study. For example, with a different pain scale, the Womack score, the observed difference was not statistically significant. Importantly, the significant difference observed was lost at the 12-month mark.
LUPUS, MYOSITIS, AND SYSTEMIC SCLEROSIS
Humorously, Pillinger admitted that lupus, myositis, and systemic sclerosis are not usually diseases you would put together in a presentation due to their distinct pathologies. However, he noted, one element that ties these complex conditions together is an approach that aims to treat them all: CD19 CAR-T cell therapy.
Pillinger gave credit to a study by Müller et al.6 for “taking CAR-T cell therapy out of oncology and into rheumatology”. In this study, CAR-T cell therapy in patients with lupus was associated with normalization of key markers such as disease activity score, anti-DNA antibodies, urine protein,
and C3 after a single treatment, with these improvements persisting for at least 24 months, essentially putting patients into remission. Similar benefits were reported for patients with myositis, with normalization of Muscle Testing scores and extra muscular symptoms. Again, in patients whose systemic sclerosis disease activity is down, and strikingly, in 6 months, the Rodnan skin score could improve dramatically.
The number of patients who will be treated with CD19 CAR-T cell therapy remains small, and therefore, conducting controlled studies will be difficult
Comparing CD19 CAR-T cell therapy to Alexander the Great cutting the Gordian knot, Pillinger explained that you don’t have to understand the subtleties of the way the knot is tied, whether it’s a lupus knot or a myositis knot, whether it’s a hemp knot or a cotton knot, he just cut right through it. That's similar to what CD19 CAR-T cell therapy does, it seems to “cut through” these complex diseases. However, he stressed that it is very time-consuming and costly. Furthermore, this therapy requires chemotherapy and may have long-term side
This marks the first randomized, double-blind, placebo-controlled trial for IgG4related disease, and the results demonstrate significant efficacy
effects that we are unaware of. Given these challenges, the number of patients who will be treated with CD19 CAR-T cell therapy remains small, and therefore, conducting controlled studies will be difficult.
TWO DISEASES WITHOUT APPROVED TREATMENTS
Whilst there are treatments that address the symptoms of Sjögren’s syndrome, such as eye drops, there is currently no agent that targets the underlying biology of the disease. Pillinger explained that Sjögren's syndrome presents in various forms. There are systemic, more severe cases that clinicians “throw the kitchen sink at” with their approach to treatment options. There are also the more typical cases of Sjögren’s syndrome, where patients are referred to as having a high symptom burden, dry eyes, fatigue, and pain. With the latter, Pillinger described how many clinicians have become somewhat nihilistic, assuming these symptoms will not respond to any treatment. However, this year, several studies have explored targeting the CD40 ligand co-stimulatory pathway and antigen presentation as a potential treatment for Sjögren's syndrome. One potential treatment is an antibody called iscalimab. This agent has been tested in both high-disease activity patients and high-symptom burden patients.7
In both patient groups, iscalimab outperformed placebo. In particular, in the high symptom burden group, iscalimab improved fatigue and, strikingly, improved dryness, something that Pillinger admitted having long believed was untreatable. These findings suggest that targeting T cells through the CD40/ CD40 ligand pathway may offer an effective approach to treating Sjögren’s syndrome.
Enter this first serious Phase III clinical trial for IgG4 disease with inebilizumab, a monoclonal antibody that targets the same CD-19 on B cells as CD19 CAR-T cells.8 In this trial, inebilizumab led to an 87% reduction in flare risk compared to placebo. 87%
Finishing the session with research “ripped from the headlines”, Pillinger highlighted a breakthrough in the treatment of IgG4-related disease. Currently, there are no approved therapies for this condition, and patients often relapse with steroid treatment. Rituximab is another option, but robust supporting data is still lacking. Enter this first serious Phase III clinical trial for IgG4 disease with inebilizumab, a monoclonal antibody that targets the same CD-19 on B cells as CD19 CAR-T cells.8 In this trial, inebilizumab led to an 87% reduction in flare risk compared to placebo. All key
We are embarking on an “extraordinary therapeutic adventure”, with many more remarkable developments to be expected in the coming years
References
1. Cope A P et al. Abatacept in individuals at high risk of rheumatoid arthritis (APIPPRA): a randomised, doubleblind, multicentre, parallel, placebocontrolled, phase 2b clinical trial. The Lancet. 2024;403(10429):838-49.
2. Rech J et al. Abatacept inhibits inflammation and onset of rheumatoid arthritis in individuals at high risk (ARIAA): a randomised, international, multicentre, double-blind, placebocontrolled trial. The Lancet. 2024;403(10429):850-9.
secondary endpoints were met, including reduced use of glucocorticoids. This marks the first randomized, double-blind, placebocontrolled trial for IgG4-related disease, and the results demonstrate significant efficacy.
CONCLUSION
The enlightening whirlwind tour of key research published in 2024 concluded with Pillinger reminding the audience that “the other 99% of important information” had been left out. He emphasized that his key takeaway from preparing for this session was that we are embarking on an “extraordinary therapeutic adventure”, with many more remarkable developments to be expected in the coming years. With apologies to Shakespeare, Pillinger closed by exclaiming, "O brave new world... that has such treatments in it!"
3. Cipolletta et al. Risk of venous thromboembolism with gout flares. Arthritis Rheumatol. 2023;75(9):1638-47.
4. Cipolletta E et al. Short-term risk of cardiovascular events in people newly diagnosed with gout. Arthritis Rheumatol. 2024;DOI:10.1002/art.42986.
5. Kingsbury SR et al. Pain reduction with oral methotrexate in knee osteoarthritis, a pragmatic phase iii trial of treatment effectiveness (PROMOTE): study protocol for a randomized controlled trial. Trials. 2015;16:77.
6. Müller F et al. CD19 CAR T-cell therapy in autoimmune disease-a case series with follow-up. New England Journal of Medicine. 2024;390(8):687-700.
7. Fisher BA et al. Safety and efficacy of subcutaneous iscalimab (CFZ533) in two distinct populations of patients with Sjögren's disease (TWINSS): week 24 results of a randomised, double-blind, placebo-controlled, phase 2b dose-ranging study. Lancet. 2024;404(10452):540-53.
8. Stone JH et al. Insights into the design and study population of mitigate: the first multinational randomized controlled clinical trial in IgG4 related disease (IgG4-RD), evaluating the efficacy and safety of inebilizumab. Presentation POS0347. EULAR, 12-15 June, 2024.
Harnessing the Power of AI in Rheumatology Without Getting Burned
THIS year’s American College of Rheumatology (ACR) Convergence, which took place from Novemeber 14th–19th 2024 in Washington, D.C., saw dozens of fascinating sessions about the latest developments in the field, presented by leading experts from around the world. One such session, ‘Harnessing the Power of AI in Rheumatology Without Getting Burned’, sought to evaluate the abilities and limitations in the use of AI in rheumatology, analyze ways that the use of AI has the potential to impact rheumatology practice, and discuss the future of rheumatology in the age of AI.
This session, moderated by Genessis Maldonado, Vanderbilt University Medical Center, Nashville, Tennessee, and Bernard Ng, Veteran Affairs, Seattle, Washington, delved into the intersection of AI and rheumatology, and explored the transformative potential that AI holds in the diagnosis, treatment, and management of rheumatic diseases. The various speakers gave the audience a comprehensive overview of various AI practical applications, emphasizing the revolutionary impact on healthcare within the rheumatological domain.
IMPACT OF AI IN RHEUMATOLOGY
After an introduction by the moderators, Bella Mehta, Hospital for Special Surgery, Weill Cornell Medicine, Jersey City, New Jersey, began her presentation on the impact of AI in rheumatology. She provided an insightful exploration of AI’s transformative role in healthcare, particularly in enhancing clinical research and practice.
To begin with, Mehta introduced AI concepts by explaining the progression from data handling to advanced AI techniques, including machine learning, deep learning, and large language models (LLM). She emphasized that
AI technologies perform tasks that mimic human intelligence
these technologies perform tasks that mimic human intelligence, such as predictions, decision-making, and data analysis.
Highlighting the surge in healthcare data (approximately 40–50 exabytes), she went on to point out how electronic medical records (EMR) and increasing AI-related publications reflect the growing relevance of data in shaping policy and research. Using examples like supervised and unsupervised machine learning, Mehta additionally illustrated AI’s ability to classify and analyze data. A key example was a study predicting 90-day mortality post-hip arthroplasty using community-level social determinants of health, revealing that such variables often outweigh race in importance.
The discussion went on to cover the use of deep learning for histopathological analysis of synovial
tissue, demonstrating AI’s potential to assess inflammation in diseases like rheumatoid arthritis (RA). The algorithm trained for cell density prediction has clinical implications for distinguishing between conditions such as RA and osteoarthritis (OA).
Mehta concluded by spotlighting LLMs’ role in natural language processing for patient education and clinical decision support. These models exemplify how AI can bridge gaps in understanding medical conditions and treatments. This presentation underscored AI’s transformative potential in rheumatology, from predictive analytics to enhancing diagnostic precision and patient care. She also stressed the importance of collaboration between AI experts and clinicians to maximize the utility of these advancements.
AI-DRIVEN CHANGES IN RHEUMATOLOGY IMAGING
Amanda Nelson, University of North Carolina at Chapel Hill, took to the stage next to discuss the changes currently taking place in the field. The exponential increase in publications on AI and deep learning, particularly in rheumatology, was highlighted during this talk. Much of the research focuses on RA and OA, though applications extend to other diseases. Nelson’s work integrates clinical datasets, imaging, biochemical, and other clinical data to improve patient care.
A key area of focus is distinguishing OA progressors from non-progressors using AI tools to analyze imaging and clinical features.
AI-generated ‘change maps’ track disease progression over time, offering insights for clinical trials and treatment effectiveness
AI can enhance decision-making in rheumatology by efficiently processing large datasets, identifying patterns, and aiding in diagnosis. For example, convolutional neural networks have been employed to classify different types of arthritis, such as seropositive and seronegative RA or psoriatic arthritis, using pre-trained models finetuned on rheumatology-specific data. These tools can also automatically score features like osteitis or synovitis, saving time and providing consistent results.
Sequential imaging analysis is another promising application, described Nelson, where AI-generated ‘change maps’ track disease progression over time, offering insights for clinical trials and treatment effectiveness. Beyond imaging, AI has been applied to pathology, where algorithms trained on annotated slides show high accuracy in identifying and classifying features like glomeruli.
Challenges remain, including the need for high-quality, representative datasets, and strategies for managing missing data. Pre-trained models often carry biases, and external validation is essential to ensure generalizability. Nelson stressed collaboration with data scientists and understanding AI tools to apply them appropriately.
AI has the potential to transform rheumatology by streamlining workflows, improving diagnostics, and aiding in clinical research; this much was clear throughout Nelson’s talk. However, clinicians must stay informed about AI’s capabilities and limitations to ensure its effective implementation. Nelson encouraged further education in AI to enhance its integration into research and practice.
CROSSING THE PRECISION GAP IN RHEUMATOLOGY WITH AI
The final part of this insightful session was delivered by John Isaacs, Newcastle University, UK, and covered the precision gap in this revolutionary technology. Though not a specialist in AI himself, Isaacs was able to provide valuable insights into the role AI plays and will go on to play in the future.
Isaacs highlighted the potential of AI in advancing rheumatology through precision medicine. AI’s core function is identifying patterns in data, enabling insights into an individual’s exposome, genomics, and epigenetics. He pointed out, agreeing with previous speakers, that this capability has already shown promise in other fields, like oncology, and offers opportunities to transform rheumatology.
This portion of the session outlined elements of robust AI analysis, beginning with data acquisition. High-quality, large, and diverse datasets are crucial, requiring collaboration across institutions and regions. Preprocessing, including cleaning and harmonizing data, addresses issues like
missing values and inconsistencies. Feature selection helps identify variables that distinguish meaningful patterns, and iterative machine learning models refine clustering and classification. However, external validation is vital to ensure models work beyond their original datasets, which is often overlooked.
Challenges in AI applications include overfitting, underfitting, and the limitations of ‘black box’ models. Explainable AI techniques, such as SHAP (SHapley Additive exPlanations), enhance model transparency, fostering trust and interpretability, which are particularly critical in medical contexts. Ethical considerations, including data privacy and consent, were emphasized, noting that older datasets often lack patient approval for AI-based applications.
Rheumatology lags behind oncology in precision medicine due to differences in the depth of data collection, such as limited tissue biopsies and less robust outcome measures, added Isaacs. Nevertheless, AI does hold promise in treatment response prediction, clustering patient subtypes, and analyzing complex datasets. Success depends on interdisciplinary collaboration
among rheumatologists, data scientists, and legal experts, as well as adherence to transparency and reproducibility standards.
Ultimately, Isaacs told the audience that he foresees a future where AI significantly impacts rheumatology, contingent on quality data, robust algorithms, and strong team science.
CONCLUDING REMARKS
Closing with an enlightening question and answer session with the audience, this session at ACR 2024 shed light on the potential of AI in the field of rheumatology. As technology continues to advance, AI will undeniably have a vast impact on the field, shaping the future of rheumatological diagnosis, treatment, and disease management.
AI does hold promise in treatment response prediction, clustering patient subtypes, and analyzing complex datasets
Abstract Reviews
This collection of abstracts showcases the cutting-edge research presented at the American College of Rheumatology (ACR) Convergence 2024. Written by the presenters themselves, this rich collection offers a taste of the current developments nationally and internationally to impact patient outcomes.
Management Practices for Raynaud’s Phenomenon in Patients with Systemic Sclerosis: Real-World Data
from Community-Based Practices in the
United States
Authors: *Gulsen Ozen,1 Sofia Pedro,2 Robyn T. Domsic,3 Kaleb Michaud2,4
1. University of Iowa Health Care, Iowa City, USA
2. FORWARD, The National Databank for Rheumatic Diseases, Wichita, Kansas, USA
3. University of Pittsburgh Medical Center, Pennsylvania, USA
4. University of Nebraska Medical Center, Omaha, USA
*Correspondence to gulsen-ozen@uiowa.edu
Disclosure: The authors declare no conflicts of interest.
Raynaud’s phenomenon (RP) in systemic sclerosis (SSc) can lead to chronic digital ischemia, ulcerations, and necrosis with significant pain and hand function loss. Not only the most common and earliest SSc manifestation, SSc-RP also has the highest patient-reported disease impact on quality
of life. Early interventions for RP can have an important impact on altering the disease course by preventing ischemia-reperfusion injury and subsequent oxidative stress with further endothelial dysfunction and fibrosis in SSc.
METHODS
This study describes the practices for SScRP management among community-based rheumatologists in the US. Rheumatologistdiagnosed adult patients with SSc who were enrolled in the FORWARD study1 between 1999–2023 were assessed for the use of vasoactive medications for RP as well as medications worsening RP. Data were collected semi-annually with comprehensive questionnaires and validated using medical records. Medications for RP included calcium channel blockers (CCB), renin-angiotensin system inhibitors (losartan or lisinopril), fluoxetine, topical nitroglycerin, phosphodiesterase 5 inhibitors (PDE5i), endothelin receptor antagonists (ERA), prostaglandin analogs (PGA), and others (pentoxifylline, dipyridamole, and prazosin).
RESULTS
Overall, the study included 270 patients with SSc (approximately 83% diffuse), with a mean (standard deviation) symptom duration of 12.1 (10.6) years (30%; ≤5 years of symptoms) at enrolment. The median (interquartile range) follow-up was 3.4 (1.3–7.8) years in the cohort. During followup, 61% of patients used medication for RP, whilst 80% of patients received treatment for gastroesophageal reflux (p<0.001). The most frequently chosen group was CCBs (48%), followed by renin-angiotensin system inhibitors. About 13% and 20% of patients received RP-worsening medications while receiving or not receiving medications for RP, respectively. Advanced therapies such as PDE5i, ERA, and PGA were utilized in only 15% of the patients. The maintenance rate of RP medications was unfortunately low, and only approximately 29% of the patients remained on medications for RP throughout their follow-up.
While patients who had hypertension or who were on immunomodulatory medications were more likely to be on RP medications, patients who were at higher risk for worse vascular outcomes (such as those with early disease (≤2 years), current smokers, or patients who were Black) were less likely to be on RP medications (Figure 1A).
When looking at the medication choices from 2000–2023, CCBs remained stably the most common RP medication prescribed. However, PDE5i use has been increasing since 2019 despite remaining <10% overall (Figure 1B).
Lastly, the RP medication use based on US climate zones showed that RP medications were used more frequently in warmer climate zones like the West or Southwest US (Figure 1C), which could be driven by more frequent air conditioning use and rapid temperature changes.
Figure 1: Medication use for patients with Raynaud’s phenomenon.
Figure 1: Continued. Medication use for Raynaud's in Systemic Sclerosis by US climate zones*
A) Medications for SSc-RP by patient characteristics. B) Frequency of RP medication use in SSc by US climate zones based. Adapted from National Centers for Environmental Information.2 C) Medication use for SSc-RP by type over time. *p<0.05.
These findings suggest that, although CCBs are commonly used for SSc-RP among community-based rheumatology practices, overall SSc-RP management appears neglected (even worse than gastroesophageal reflux disease management) with low maintenance rates, low advanced therapy use rates, and significant concomitant use of RPworsening medications. The increase in PDE5i use beginning in 2019, and corresponding to generic PDE5i availability, provides face validity to this real-world data. Besides FDA non-approval of advanced therapies (PDE5i, ERA, or PGA) for SSc-RP or its complications, lack of experience and guidelines for the
management of SSc-RP and its complications play a significant role in the care gap of SSc-vasculopathy in community-based rheumatology practices. More education is needed to improve outcomes in SSc, especially in the setting of workforce deficits in rheumatology.
References
1. Wolfe F, Michaud K. The National Data Bank for Rheumatic Diseases: a multi-registry rheumatic disease databank. Rheumatology (Oxford). 2011;50:16-24.
2. National Centers for Environmental Information. U.S. climate regions. Available at: https://www.ncei. noaa.gov/access/monitoring/reference-maps/usclimate-regions. Last accessed: 14 October 2024.
Machine Learning-Based Risk Stratification Tool to Predict Early Flare for
Rheumatic and musculoskeletal diseases (RMD) affect up to one-third of the UK population, are the number one cause of disability, and are one of the most common reasons for people of working age having
an increased number of sick days or unemployment.1 Patients with RMD experience periods of exacerbation of disease, known as flares, which are associated with pain and function limitations for patients.2 If the disease flare is detected and treated late, this can lead to joint damage and reduced function.
RMD flares are unpredictable, and there is no marker identified for an impending flare. Sudden flares may lead to additional hospitalisations and follow-up visits,and decreased quality of life in general.3 However, there is currently no risk stratification model that can predict patient flare early and accurately in practice.
The authors aimed to develop and evaluate a machine learning-based risk stratification model that can predict the risk of future disease flares and guide early and accurate intervention to prevent flares in patients with RMD.
METHODS
In this study, 142,067 patients who had been diagnosed with RMD in the rheumatology department of Royal Berkshire NHS Foundation Trust (UK) from January 1, 2016–May 7, 2024 were included. This included 58,727 patients who had flares and 83,340 patients who did not have flares. The authors utilised patient blood test results, demographic information, electronic patient-reported outcomes scores, comorbidity, weight, and height. They developed a time series dataset and applied Long Short-Term Memory networks and neural networks to forecast the risk of flare before their future clinics.
RESULTS
The authors conducted predictive modelling to forecast flare and non-flare events using data collected prior to patients' upcoming clinic appointments. The dataset was split into training and testing sets based on observations taken 3 months and 6 months
before the clinic visit. Their applied Long Short-Term Memory-based model achieved 89.32% accuracy and 0.76 Area Under the Receiver Operating Characteristic Curve (AUROC), predicting flare and non-flare events 6 months before the clinics, and 81.93% accuracy and 0.68 AUROC 3 months before. The results are summarised in Table 1
CONCLUSION
The authors’ model can predict future flare and non-flare events with 89.93% accuracy 6 months in advance. Further work includes using advanced data processing methods to handle missing values to improve accuracy, especially for predictions 3 months in advance. If implemented in practice, the flare-risk stratification model can be used to aid patients and clinicians in prognosticating the risk of flares quickly. This flare-risk prediction can aid the patients and clinicians in recognising if they are at a trend of flares or reduction in the efficacy of their treatment. With the informed risk prediction presented early and more accurately,
Prediction 6 months in advance is more accurate than 3 months in advance. LSTM exhibited superior performance in average accuracy and AUROC compared to NN.
AUROC: Area Under the Receiver Operating Characteristic Curve; LSTM: Long Short-Term Memory; NN: neural networks.
Table 1: Performance of Long Short-Term Memory and neural networks on data from 3 months and 6 months before the clinic visit.
the patient will be able to book an early appointment with a specialist so that early interventions can be put in place to prevent
References
1. Scott IC et al. Rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis epidemiology in England from 2004 to 2020: an observational study using primary care electronic health record data. Lancet Reg Health Eur. 2022;23:100519.
2. Yiming S et al. Advancing precision rheumatology:
flares in a timely way. Clinicians can identify patients at high risk of flares so interventions such as intensifying or changing medication can be in place before flare happens.
applications of machine learning for rheumatoid arthritis management. Front Immunol. 2024;15:1409555.
3. De Cock D et al. Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs). Ther Adv Musculoskelet Dis. 2022;14:1759720X221105978.
Effect of a Whole Food Plant-Based Diet in Patients with Gout: A Pilot Randomized Controlled Trial
Authors: *Anna Kretova,1 Carlijn Wagenaar,1,2,3
Wendy Walrabenstein,1,2 Daisy Vedder,1,2,3
Dirkjan van Schaardenburg,1,2,3 Martijn Gerritsen1,2,3
1. Reade Rheumatology Center, Amsterdam, the Netherlands
2. Amsterdam University Medical Center (UMC), the Netherlands
3. Amsterdam Rheumatology and Immunology Center, the Netherlands
*Correspondence to a.kretova@reade.nl
Disclosure: The authors declare no conflicts of interest.
Acknowledgements: The authors would like to thank the Vermeer 14 Foundation for financial support of the study.
Keywords: Diet, gout, health behaviors, lifestyle, nutrition, urate, uric acid.
An unhealthy diet is an important modifiable risk factor for hyperuricemia and gout and is also associated with obesity and metabolic syndrome (MetS), known risk factors for gout as well as for cardiovascular disease (CVD).1 The prevalence of CVD is considerably elevated in patients with gout.2 Nutrition plays a role in hyperuricemia and inflammation,
directly and through metabolic dysregulation, liver, kidney, and gut health.3-7
A Mediterranean-style whole food plantbased diet (WFPD) has been shown to be effective for the treatment of other MetS- and obesity-related diseases,8-10 as well as (inflammatory) joint diseases, such as rheumatoid arthritis and osteoarthritis, leading to significantly decreased disease activity and improved metabolic status in both patient groups.11, 12 The authors, therefore, aimed to investigate the effect of a dietary intervention based on a WFPD on serum uric acid (SUA), gout disease activity, and cardiovascular risk in patients with gout.
METHODS
In the DIEGO (A DIEt for the treatment of GOut) pilot randomized clinical trial, patients with gout, hyperuricemia (males ≥0,42 mmol/L and females ≥0,36 mmol/L), abdominal obesity (waist circumference of ≥102 cm for males and ≥88 cm for females), and not receiving urate-lowering therapy were assigned to the DIEGO WFPD intervention group or a usual care control group. The DIEGO group received individual counseling from a registered dietitian (60 min at baseline, 30 min in Week 2, 4, 8, and 12) and followed a Mediterraneanstyle WFPD for 16 weeks. Participants
Table 1: Primary and secondary outcomes of the DIEGO trial.
Gout-related outcomes
Anthropometric measurements
Table 1 continued
Continuous variables are reported as mean (SD) when normally distributed or as median (IQR) when skewed. Between-group differences shown at the end of the dietary intervention were determined using the linear-mixed model adjusted for baseline values. Outcomes were similar after adjusting for sex, age, and baseline BMI (weight, BMI, and waist circumference not adjusted for BMI), except pain (non-significant after adjustment). Within-group differences were assessed with a paired t-test when normally distributed or a Wilcoxon rank test when skewed. For variables in which model assumptions were not met (†) a linear-mixed model was performed after log(x + 1) transformation and between differences were reported as median difference determined using a Wilcoxon test (p values from the linear mixed model are shown, all were similar to the Wilcoxon test). VAS scores range from 0 (least) to 10 (worst). Significant within-group differences were reported (*) when p<0.05.
*Significant within-group differences.
†Variables in which model assumptions were not met.
were allowed to use their usual gout flare medication during a gout flare. The primary outcome was the SUA level. Secondary outcomes included gout disease activity, cardiovascular risk factors, and several other metabolic markers. An intention-to-treat analysis with a linear mixed model, adjusted for baseline values, was used to analyze the between-group differences of primary and secondary continuous outcomes at 16 weeks.
RESULTS
Of 54 people screened, 36 were randomized and 31 completed the study (DIEGO group: n=18). Overall, 92% of participants were male, with a mean (SD) age of 52 (12) years and a mean (SD) BMI of 33 (4) kg/m2. After 16 weeks, the DIEGO group had significantly lower SUA levels (-0.03 mmol/L: 95% CI: -0.06 to -0.00, p=0.03; -0.05 mmol/L: 95% CI -0.08 to -0.02, p=0.004; after adjustment for age, sex, and BMI) as compared to the control group (Table 1). In total, 23 gout flares occurred during the study, 11 in the DIEGO group and 12 in the control group. The mean (SD) duration (days) and flare intensity (Visual Analogue Scale [VAS] range 0 least to 10 worst) in the DIEGO group were 5.6 (2.3) and 6.2 (1.8), respectively, versus 4.6 (2.7) and 6.7 (1.6) in the control group.
Overall, gout severity and pain (VAS range 0 least to 10 worst) were significantly lower in the DIEGO group versus the control group: -2.0 (95% CI: -6.0 to -1.0) and -2.0 (95% CI: -5.0 to -0.0), respectively. Compared to the control group, the DIEGO group had a lower body weight, reduced waist circumference, and improved low-density lipoprotein cholesterol at the end of the study. The changes in systolic blood pressure and hemoglobin A1C were not significantly different between the groups; however, the systolic blood pressure and hemoglobin A1C reduced significantly within the DIEGO group and not in the control group. C-reactive protein and diastolic blood pressure remained unchanged. No serious adverse events occurred during the study.
CONCLUSION
The Mediterranean-style WFPD significantly decreased SUA in patients with gout and abdominal obesity. In addition, following the Mediterranean-style WFPD resulted in decreased gout severity and pain, significant weight loss, decreased waist circumference, and improved low-density lipoprotein cholesterol, thus reducing the risk for CVD.
References
1. Choi HK et al. Population impact attributable to modifiable risk factors for hyperuricemia. Anthritis Rheumatol. 2019;72(1):157-65.
2. Hansildaar R et al. Cardiovascular risk in inflammatory arthritis: rheumatoid arthritis and gout. Lancet Rheumatol. 2021;3(1):e58-70.
3. Dalbeth N et al. Gout. Nat Rev Dis Primers. 2019;5(1):69.
4. Major TJ et al. An update on the genetics of hyperuricaemia and gout. Nat Rev Rheumatol. 2018;14(6):341-53.
5. Hall KD et al. Effect of a plant-based, low-fat diet versus an animal-based, ketogenic diet on ad libitum energy intake. Nat Med. 2021;27(2):344-53.
6. Furman D et al. Chronic inflammation in the etiology of disease across the life span. Nat Med. 2019;25(12):1822-32.
7. Ramos-Lopez O et al. The role of nutrition on metainflammation: insights and potential targets in communicable and chronic disease management. Curr Obes Rep. 2022;11(4):305-35.
8. Ornish D et al. Intensive lifestyle changes for reversal of coronary heart disease. JAMA. 1998;280(23):2001-7.
9. Walrabenstein W et al. A multidisciplinary lifestyle program for rheumatoid arthritis: the ‘Plants for Joints’ randomized controlled trial. Rheumatology. 2023;62(8):2683-91.
10. Barnard ND et al. low-fat vegan diet and a conventional diabetes diet in the treatment of type 2 diabetes: a randomized, controlled, 74-wk clinical trial. AM J Clin Nutr. 2009;89(5):1588S-96S.
11. Barnard ND et al. A Mediterranean diet and low-fat vegan diet to improve body weight and cardiometabolic risk factors: a randomized, crossover trial. J Am Nutr Assoc. 2022;41(2):127-39.
12. Walrabenstein W et al. A multidisciplinary lifestyle program for metabolic syndrome-associated osteoarthritis: the "Plants for Joints" randomized controlled trial. 2023;31(11):1491-500.
Improving Prior Authorization Efficiency with Artificial Intelligence: A Study on Rheumatology Investigations
Authors: *Humeira Badsha,1 Tanishka Agarwal,2
Arun J,3 Sumanth C. Raman3
1. Dr. Humeira Badsha Medical Center, Dubai, United Arab Emirates
2. Dubai International Academy, Dubai, United Arab Emirates
3. Algorithm Health, Chennai, India
*Correspondence to doctorbadsha@gmail.com
Disclosure: The authors have declared no conflicts of interest.
The prior authorization (PA) process in healthcare, while necessary for ensuring the
and Treatments
medical necessity and cost-effectiveness of treatments, often results in significant delays. This study explores the potential of AI to streamline the PA process, based on research conducted by Humeira Badsha and colleagues. The study compares the efficiency of a proprietary AI rule engine, supported by an OpenAI-based machine learning (ML) model, against traditional methods used by insurance companies. The results indicate that AI can significantly reduce the time required for authorization, thereby improving patient care.
INTRODUCTION
The PA process is a critical step in healthcare, ensuring that patients receive necessary treatments and medications. Mandated by insurance companies, this process confirms
the medical necessity and cost-effectiveness of prescribed treatments. However, it often results in significant delays, potentially leaving patients at risk of untreated conditions. Recent advancements in AI offer promising solutions to streamline and expedite the PA process.
BACKGROUND AND PURPOSE
Patients with chronic autoimmune conditions often require expensive treatments that necessitate PAs. According to a 2023 American Medical Association (AMA) survey, 94% of physicians reported treatment delays due to PA, with 78% of patients abandoning treatment as a result.1 A 2020 survey of rheumatic patients revealed that 48% required PA for their medications.2 The American College of Rheumatology's 2020 position statement emphasizes the need to modernize and streamline the PA process.3 This study aims to compare the efficiency of an AI rule engine against traditional methods used by insurance companies in processing PAs for rheumatology investigations and medications.
METHODS
This study involved 50 patients from a rheumatology clinic who required PA for investigations or treatments with biological medications. Anonymized medical reports were uploaded into an AI rule engine and simultaneously sent to insurance companies for approval. The AI engine analyzed the reports to classify the appropriateness of the patients' diagnoses and requested treatments, and this data was compared to the insurance companies' responses.
The Algorithm Health system employs a concept called Guided AI. A medical preprocessing engine handles the initial processing of data before it is fed into the ML model. This preprocessing ensures significantly greater accuracy by avoiding many of the common failings of pure AI models. The proprietary data extraction model created by Algorithm Health
ensures complete and appropriate extraction of digitized data from medical records, enhancing the preprocessing stage. The integration of the data extraction model with the preprocessing engine and the customized ML model is the unique selling proposition of Algorithm Health’s platform.
RESULTS
The AI rule engine demonstrated remarkable efficiency. Among the 41 investigation approval requests, the AI engine deemed 95% appropriate within a minute, whereas insurance companies approved only 82.9%, with 17.1% still pending and 2.4% rejected outright. Approval times varied, with some investigations taking over 2 weeks. Additionally, 29.2% of the investigations required further queries. For the 43 medication approval requests, the AI engine matched every diagnosis and treatment plan, but only 81.3% were approved by insurance companies, with 18.6% pending. Further queries averaged a delay of 5 days.
CONCLUSION
This study highlights significant delays in the PA process, which can adversely impact patient health. The AI rule engine demonstrated the potential to significantly expedite the process by quickly identifying appropriate requests and reducing patient wait times. AI can also help eliminate unjustified requests, further streamlining the process.
IMPLICATIONS FOR HEALTHCARE
Integrating AI into the PA process offers several benefits, as highlighted by recent studies and expert opinions:
1. Efficiency: AI can rapidly process and analyze patient data, reducing approval times significantly. According to a report by McKinsey, AI can increase productivity and efficiency in care delivery,
allowing healthcare systems to provide more and better care to more people.4
2. Accuracy: AI ensures that only appropriate requests are approved, eliminating unnecessary denials. The National Academy of Medicine (NAM) identified three potential benefits of AI in healthcare: improving outcomes for both patients and clinical teams, lowering healthcare costs, and benefiting population health.5
3. Reduced burden: Streamlining the PA process allows healthcare professionals to focus more on patient care. AI can help reduce the paperwork burden that often leads to burnout among healthcare workers.6
4. Improved patient outcomes: AI can assist in early diagnosis and treatment, leading to better patient outcomes. For example, AI can help with preventive screenings and risk assessments, identifying potential health issues before they become severe.5
5. Cost savings: By reducing delays and improving efficiency, AI can help lower healthcare costs. This is particularly important in resource-poor settings where access to healthcare is limited.4,5,7
6. Enhanced patient experience: AI can improve the patient experience by providing faster responses and more personalized care. For instance, AI can help patients better understand their health conditions and treatment options.4,6,7
References
1. American Medical Association (AMA). AMA survey indicates prior authorization wreaks havoc on patient care. 2024. Available at: https://www.ama-assn.org/ press-center/press-releases/ama-survey-indicatesprior-authorization-wreaks-havoc-patient-care. Last accessed: 13 June 2024.
2. American College of Rheumatology (ACR). Prior authorization & rheumatic disease. 2023. Avaialable at: https://rheumatology.org/patient-blog/how-priorauthorization-affects-individuals-with-rheumaticdisease. Last accessed: 13 June 2024.
3. American College of Rheumatology (ACR). ACR Releases position statement on prior authorization 2020. Available at: https://rheumatology.org/pressreleases/acr-releases-position-statement-on-priorauthorization. Last accessed: 13 June 2024.
4. McKinsey & Company. Transforming healthcare with AI: The impact on the workforce and organizations. 2020. Available at: https://www.mckinsey.com/ industries/healthcare/our-insights/transforminghealthcare-with-ai. Last accessed: 13 June 2024.
5. National Academy of Medicine. AI in healthcare: The future of patient care and health management. 2024. Available at: https://digest.headfoundation. org/2024/07/10/ai-in-healthcare-the-future-ofpatient-care-and-health-management/#easyfootnote-1-41966. Last accessed: 13 June 2024.
6. World Health Organization (WHO). Harnessing artificial intelligence for health. 2024. Available at: https://www.who.int/teams/digital-health-andinnovation/harnessing-artificial-intelligence-forhealth#:~:text=WHO's%20vision%20is%20to%20 foster,no%20one%20is%20left%20behind. Last accessed: 13 June 2024.
7. Powell A. Risks and benefits of an AI revolution in medicine. 2020. Available at: https://news.harvard. edu/gazette/story/2020/11/risks-and-benefits-of-anai-revolution-in-medicine/. Last accessed: 13 June 2024.
A Qualitative Exploration of Oral Healthcare Needs Amongst Canadian Patients with Rheumatic
Diseases and Their Providers
Authors: Chrysi Stavropoulou,1 Corrie Billedeau,2 Jennifer Protudjer,1 *Carol A Hitchon1
1. University of Manitoba, Winnipeg, Canada
2. Patient Partner Winnipeg, Canada
*Correspondence to carol.hitchon@umanitoba.ca
Disclosure: Hitchon has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Sanofi; has participated on a Data Safety Monitoring Board or Advisory Board of Fresenius-Kabi and AstraZeneca. The other authors declare no conflict of interest.
Patients with autoimmune rheumatic diseases (RD) have a high prevalence of oral manifestations and/or oral side effects from immunomodulatory medications.1 These factors combined with challenges impacting oral self-care can adversely impact oral health and overall quality of life.2 Poor oral health, in particular periodontitis, may contribute to chronic disease, including rheumatic disease, highlighting the importance of maintaining optimal oral health.
OBJECTIVES
The study objectives were to explore how patients with RDs perceive their oral health, to describe how patients and their health care providers (HCP) approach oral care (selfcare and professional dental care) and any challenges/solutions related to this oral care, and to determine preferences for delivering oral health knowledge to patients and HCPs.
METHODS
Patients with RD and HCPs participated in semi-structured interviews conducted virtually. Patients had a variety of RDs, including rheumatoid arthritis and systemic autoimmune inflammatory disease. HCPs included adult and pediatric rheumatologists and an oral pathology dental specialist. Interviews were analyzed for common themes. After interviewing nine patients, no additional themes emerged.
RESULTS
All patients that were interviewed reported oral health concerns, the most common being gingival bleeding or recession, dry mouth, multiple tooth fractures, caries, fillings or crowns, oral ulcers, and temporomandibular joint issues. Most (56%) reported challenges with professional oral care.
Four themes were identified.
1. Oral health care perceptions: patients have multiple oral health issues, and there are challenges with professional oral health care. (Patient quotes: “My oral health, it’s not good”; “I have trouble opening my mouth wide enough for long periods of time”)
2. Oral care requires creativity and commitment: multiple strategies were used to overcome physical limitations and address oral symptoms; and financial obstacles exist. (Patient quotes: “Electric toothbrushes are too skinny to hold [and are controlled by] switches using your thumb ... mouth-operated switches would be easier”; “How much money are you going to spend on your mouth?”)
3. Communication on oral health and RD (barriers and solutions): there is a lack of awareness of the links between oral health and chronic disease, limited evidence-based guidelines relating to oral care for patients with rheumatic disease, and varied preferred communication strategies. (Patient quote: “I didn’t get a lot of information in the beginning… much was by trial and error”; HCP quotes: from a rheumatologist, “In my training, there is very limited oral health”; from a dental specialist, “Conferences should be interprofessional and patient-centered… we need to bring this information to practice.”)
4. Need for change in models of care: lack of inter-professional communication dictates a need for self-advocacy and improved models of care. Multidisciplinary team-based models are suggested. (Patient quote: “I make sure all my caregivers have got the same information so we can work together”; HCP quote: “We have to work as a group […] so if a patient develops [a condition] with an oralsystemic link we can work together.”)
CONCLUSION
Patients with RDs perceived substantial challenges with their oral health and professional dental care. Multiple dental products and creative strategies were utilized by the patients to overcome these challenges. Current educational resources were described as limited and unreliable. A multi-pronged communication strategy was suggested by the patients. An inter-professional team with holistic approach was proposed by patients and HCPs to help establish trusting relationships and more effective care.
References
1. Gualtierotti R et al. Main oral manifestations in immune-mediated and inflammatory rheumatic diseases. J Clin Med. 2019;8(1):21.
2. Schmalz G et al. Oral-health-related quality of life in adult patients with rheumatic diseases-a systematic review. J Clin Med. 2020;9(4):1172.
VIVA QI – Vaccination In Vasculitis: Applying a Quality Improvement Approach
Authors: Alexandra Mah,1 *Stephen Williams,2 Stephanie Garner,2 Aurore Fifi-Mah2
1. Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland
2. Cumming School of Medicine, University of Calgary, Alberta
*Correspondence to stephen.williams1@ucalgary.ca
Disclosure: Funding for this research was provided by a grant from Pfizer. Fifi-Mah has received payment or honoraria from Otsuka, Organon, Janssen, Sandoz, Pfizer, Novartis, and AbbVie; payment for expert testimony from the College of Physicians of Alberta; support for attending meetings and/or travel from Frenesius Kabi; and is in the leadership or fiduciary role for
Canadian Rheumatology Association. The other authors declare no conflicts of interest.
Vasculitis is an umbrella term encompassing approximately 20 rare but serious diseases that are characterized by autoimmune inflammation and damage of the blood vessels. Patients living with vasculitis are considered immunocompromised and
require further immunosuppression for the management of their autoimmune condition to prevent organ damage and death. Without immunosuppression, the mortality rate of some forms of vasculitis can reach 90% over 2 years. As a result of these two factors, there is an increased risk of vaccinepreventable diseases, which can result in increased morbidity and mortality in this patient population.1 Infection is, in effect, the leading cause of death in vasculitis.2-5 Due to this risk, vaccination is highly recommended for all patients with vasculitis6-7 but due to the rarity of this condition, a baseline rate of vaccination was not yet readily available. In this prospective quality improvement study, the authors’ aim is to provide Canada’s first baseline rate of vaccination in patients with vasculitis and implement a multidisciplinary strategy involving the patient’s rheumatologist and community pharmacists to improve vaccination rates.
METHODS
Hundred and three patients, between the ages of 18–89 (58% female), attending Calgary’s South Health Campus rheumatology clinic in 2023 were initially recruited to build a vaccination database. This database was created by reviewing papers and electronic charts. This determined the baseline vaccination status against pneumonia (PPSV23, PCV13, PCV20), shingles (RZV), tetanus (Tdap), hepatitis B, COVID-19, and influenza. Data pertinent to vasculitis subtype, treatment type, and demographics was also recorded. Patients were then contacted and provided with an overview and education of their missing vaccinations. All 103 patients who agreed to participate had their pharmacy of choice contacted by a member of the research team for their missing vaccinations. In-clinic reminders were also provided by intake nurses at the patient’s next visit. The vaccination status of patients in the database was reviewed at 1 year (2023–2024) to determine what improvements occurred in the overall
vaccination rate. Patients with an incomplete/ partial vaccine status were re-contacted to determine reasons for missing their vaccination(s) and were provided assistance in completing their vaccine series if they accepted (re-contacting the pharmacy, referral to public health, etc).
RESULTS
The baseline and final vaccination statistics of the 103 patients participating in VIVA QI can be seen in Table 1. The greatest vaccinated subgroup were those aged >65. The majority of participants selfidentified as being White (79%), lived in a region with >100,000 people (80%), and had a primary care provider (89%).
CONCLUSION
In this study, vaccination rates increased throughout all measured vaccines. The greatest improvement in vaccination rate occurred in vaccines which pharmacies could offer for free (influenza 34% increase, 233% year-over-year (YoY); COVID-19 26% increase, 68% YoY; PPSV23 16% increase, 59% YoY; and Tdap 14% increase, 25% YoY). Eighty-five percentage of the patients reported that the greatest barrier to vaccination was the cost of the vaccine. High degrees of trust were also expressed by patients regarding their healthcare providers; 91–96% of patients stated they trust their pharmacist, rheumatologist, and family physician’s opinion that vaccinations are safe. Due to VIVA QI’s multidisciplinary approach helping and educating patients, when compared to the provincial vaccination rates for the same time period, it resulted in greater vaccination rates (influenza 24.2% versus 49% and COVID-19 16.8 versus 46%, respectively). This study demonstrates the impact that a multidisciplinary approach has on a patient’s safety and care.
Table 1: VIVA-QI patient vaccination status at baseline versus after implementation of a multidisciplinary approach towards vaccination.
Pneumovax 23 (PPSV23)
Tetanus (Tdap)
Prevnar 13 (PCV13)
Hepatitis B (HepB)
Influenza (IIV3, IIV4)
Shingles (RZV)
*COVID-19: receiving less than three mRNA vaccinations.
†Hepatitis B: receiving less than three vaccines.
‡Shingles: receiving one out of two vaccines in the series.
References
1. King C et al. The complications of vasculitis and its treatment. Best Pract Res Clin Rheumatol. 2018;32(1):125-36.
2. Dagostin MA et al. Mortality predictors in ANCAassociated vasculitis: experience of a Brazilian monocentric cohort of a rheumatology center. Medicine (Baltimore). 2021;100(51):e28305.
3. Wallace ZS et al. All-cause and cause-specific mortality in ANCA-associated vasculitis: overall and according to ANCA type. Rheumatology (Oxford). 2020;59(9):2308-15.
4. Furer V et al. Incidence and prevalence of vaccine preventable infections in adult patients with autoimmune inflammatory rheumatic diseases
(77%)
(6%)‡ 18/103 (17%)
(AIIRD): a systemic literature review informing the 2019 update of the EULAR recommendations for vaccination in adult patients with AIIRD. RMD Open. 2019;5(2):e001041.
5. Theofilis P et al. Overview of infections as an etiologic factor and complication in patients with vasculitides. Rheumatol Int. 2022;42(5):759-70.
6. Bass AR et al. 2022 American College of Rheumatology guideline for vaccinations in patients with rheumatic and musculoskeletal diseases. Arthritis Care & Research. 2023;75(3):449-64.
7. Furer V et al. 2019 update of EULAR recommendations for vaccination in adult patients with autoimmune inflammatory rheumatic diseases. Ann Rheum Dis. 2020;79(1):39-52.
Interviews
AMJ had the privilege of interviewing John H Stone, Roy Fleischmann, and Daniel Wallace, who shared their expertise and experiences in advancing rheumatology care. Stone discussed his pioneering work on IgG4-related disease and his efforts to address steroid toxicity, while Fleischmann reflected on the evolution of rheumatoid arthritis treatments and the impact of JAK inhibitors. Wallace discussed recent advancements in lupus research and the importance of patient advocacy through initiatives like the Wallace Rheumatic Diseases Foundation. Together, they emphasized innovation, education, and collaboration to shape the future of rheumatology.
John H Stone Director of Clinical Rheumatology at Massachusetts General Hospital and Professor of Medicine at Harvard Medical School
Q1What inspired you to pursue a career in medicine, and how did you eventually find your way into the field of rheumatology and vasculitis?
We are on the verge of having the first approved therapy for IgG4-RD
Growing up I played football, but it quickly became clear that I probably would not become a professional player, so I began to consider other paths. My father was a cardiologist, and I was drawn to medicine because I was attracted to the idea of synthesizing science to help patients. As a young person, while thinking about my career I always envisioned that I would be taking science and bringing that to patients, though I wasn’t sure how at first. Later, when I started my first clinical trial, I realized I was doing exactly that; applying novel therapies to patients with diseases. This has been a theme for my entire career.
Initially, I thought I’d specialize in infectious diseases. During my medical training, AIDS was a major focus, and I even considered becoming an AIDS physician in Africa. However, during a rheumatology rotation in my second year of residency, I encountered a 22-year-old drummer with hearing loss, pulmonary nodules, and a positive test for a newly described antibody. My preceptor was running late, and so I got to looking in textbooks to try to figure out what my patient had. I came upon the chapter on granulomatosis with polyangiitis. That experience hooked me on rheumatology.
The diagnostic journey that both the patient and the physician face has always been very intriguing to me, the fact that rheumatic diseases are typically multi-organ diseases, and then the fact that we can treat them. Unlike some
specialties, we could treat these conditions, though often with suboptimal results, but we've been able to exert positive effects very quickly with steroids. The real promise of going into rheumatology in the early 1990s when I did was that we would be able to develop better therapies that would use a lot less steroids or replace them altogether. Ultimately, over the last few decades we’ve been doing just that; through the development of better medications, we've been able to develop better therapies and have better patient outcomes. We still use too many steroids, and that is a major interest of mine, glucuronide toxicity.
Q2You’ve been at the forefront of research on IgG4-related disease (IgG4-RD), a disease that was virtually unknown in the USA before your work. What was it like to define and develop understanding around a completely new disease?
It has been a dream to participate in the description of this disease. All of my interests have been driven from experiences with individual patients, like the 22-year-old drummer that made me a rheumatologist.
One of the very first patients I saw when I came to the Massachusetts General Hospital, Boston, USA, in 2007 was a 26-year-old woman from Casablanca, Morocco, who was referred to me to rule out Sjogren’s syndrome. She had significant swelling under her chin and enlarged submandibular glands. I have never seen anything like that, and I was transfixed by her case. I really struggled while trying to figure out what her diagnosis was. It turned out to be IgG4-RD,
Our group was the first to identify that the disease could involve the aorta and the thyroid gland
which didn't even really have a name at the time. It had only been recognized as a unique disease in 2003, and almost no one in the USA knew about that condition. That really caused my career to veer off on to what has been an incredibly exciting 17 years studying IgG4-RD. I've seen hundreds of patients with the condition at the Massachusetts General Hospital Center for IgG4-RD. Like my work with antineutrophil cytoplasmic antibody-associated vasculitis and giant cell arteritis, I’ve been involved in the development of new therapies for IgG4-RD. It’s been incredibly rewarding to not only contribute to the description of a new disease but also to help discover treatments for it.
Q3
How has the research landscape changed for IgG4-RD over the years?
IgG4-RD has been a series of eureka moments. In the early years of recognition of the disease, it was simply recognizing the extent of the disease, recognizing the different organs that it can involve, and the resolution of medical mysteries that had persisted for over a century. For instance, conditions like Riedel’s thyroiditis, once thought to be an isolated inflammatory disorder of the thyroid gland, were able to be seen as part of the broader
IgG4-RD spectrum. Similarly, autoimmune pancreatitis, Kuttner’s tumor, and idiopathic orbital inflammation were also identified as manifestations of IgG4-RD.
Those first few years were about defining the disease’s extent. Then, by observing the effects of B cell depletion therapy on the immune system, sometimes just through evaluating peripheral blood samples, we began to understand the disease’s pathophysiology in significant ways. Although there are still gaps in our knowledge, we’ve made tremendous progress in a short time. Now, based on this understanding, we’re conducting worldwide, multicenter, randomized, double-blind, placebocontrolled trials, and we are on the verge of having the first approved therapy for IgG4-RD.
Q4 Your research group has made some important discoveries related to IgG4-RD. Can you talk about one or two of these discoveries and their significance for the field?
In the early understanding of IgG4-RD, much of the focus was on recognizing its presence in different organs. Our group was the first to identify that the disease could involve the aorta and the thyroid gland. These were special moments, where we kept realizing that the disease could manifest in yet another area. However, the most significant contribution so far has been recognizing that B cell depletion is a highly effective treatment for this disease.
Traditionally, and still in many parts of the world, steroids have been the cornerstone therapy for this disease, but they are far from ideal
because the disease very often targets the pancreas, making the patients at risk for diabetes and other complications of steroid use. The ability to treat them far more safely and easily with B cell depletion has been really a big step forward therapeutically. By observing what happens to patients’ immune systems after B cell depletion, we've been able to tease apart a lot of the different elements that make the disease tick. Ultimately, this understanding is going to lead to even better therapies.
We'll have even more elegant ways of shutting this disease off and hopefully curing it in the next decade
This progress has been incredibly rewarding, especially as we collaborate with investigators from all over the world. We've established wonderful collaborations with investigators in Japan, China, and Europe, and it's a revelation to understand that we're all seeing the same thing, all making the same observations, and finding great satisfaction in the impact we can make together.
Q5With the continuous development of new therapies, what advancements do you anticipate in the treatment of autoimmune and inflammatory diseases? Are there any emerging therapies that particularly excite you?
I think in the next several years, treatment strategies for IgG4-RD will continue to center around the inhibition or the depletion of B cells. Approaches like mepolizumab,
which is similar to rituximab, and new therapies that may not deplete B cells but inhibit them reversibly, such as obeximab that is now in Phase III trials, are showing promise. Cell-based therapies, including CAR-T cell approaches, are also on the horizon and could have a significant impact in the next few years.
We are currently researching the role of complement proteins in IgG4-RD, and complementbased therapies may also play a role in its treatment. Ultimately, I think we're going to understand the mechanisms of the disease far better than we do now, and we'll have even more elegant ways of shutting this disease off and hopefully curing it in the next decade or so, or at least have therapies that are far more imaginative than now.
Q6What do you see as the most pressing challenges in rheumatology over the next decade? How do you think the field will need to evolve to address these?
We need to educate patients about IgG4-RD because the disease is so insidious and progresses slowly. Many patients have the disease for months or even years before being diagnosed, during which time the affected organs can sustain permanent damage. It’s crucial to improve the education of medical practitioners, as awareness and understanding of this disease are still limited.
Moreover, there isn’t much accessible information for patients because there has been very little that has been written about the disease that is accessible at the patient level. There is a lot of misinformation on the internet, so we really need to educate practitioners and patients better than we do now.
It's also going to be important to make sure that patients have access to the new therapies that are developed. Oftentimes, these are quite expensive. Without proper measures, people worldwide, including those in Africa, South America, and even North America may not have access to these therapies if we don't take the proper actions to ensure that they do.
Q7What led you to find the IgG4ward! foundation, and can you share some of the main objectives the foundation aims to achieve?
Educating patients is crucial. For many years, I was focused on diagnosing, treating, and writing about this fascinating new condition. However, I began to notice that the patients kept coming to me with the same questions, and the new patients did not seem to be any farther along in their understanding of the disease than the patients I had managed 5 or 10 years earlier. It became clear that we weren’t doing enough to educate patients.
So the first priority for the foundation is to be a trusted source of truth for patients and for people living with IgG4-RD. We aim to do this through our website, fireside chats, and our first patientfocused gathering, the IgG4ward! Jamboree, which will be held this November. This event will bring the IgG4-RD community together and help unify our efforts to educate and support patients.
Educating physicians is equally important. The IgG4ward! foundation has established a physician’s network to connect knowledgeable doctors with patients seeking physicians specializing in IgG4-RD and to provide a forum for physicians to exchange ideas. We are also committed to facilitating research,
learning continuously, and sharing the latest information with both patients and healthcare providers.
Q8
Looking ahead, what are your long-term goals for your research? Are there any specific areas you are particularly eager to explore in the coming years?
I have really focused my career now on two major areas. First is IgG4RD, and increasingly those efforts center around the IgG4ward! foundation. I still love to practice medicine and to see patients with IgG4-RD, and I'm going to continue doing that. It's really the lifeblood of everything else that I do. The other major interest of mine within medicine is steroid toxicity, which is a major problem in the world. Again, it gets back to patient education and physician education, the development of new therapies, and inequalities with access to potential steroid therapies. I am the chairman of the Scientific Advisory Board for a company called STERITAS, which is focused on targeting steroid toxicity in a variety of ways: developing instruments to measure toxicity, helping to get new drugs improved reducing the use of steroids in clinical practice, studying steroid toxicity in health economics and outcome research, and developing tools to help patients optimize their own stereo. I think for the rest of my career my focus will be on IgG4-RD and steroid toxicity.
Roy Fleischmann
Adjunct Professor of Medicine, University of Texas Southwestern Medical Center; Co-Medical Director of Metroplex Clinical Research Center, Dallas, Texas, USA
Can you start by telling us a bit about your journey into rheumatology and what initially inspired you to specialize in this field, and what continues to drive your passion for research and patient care?
There are probably two main reasons. The first is that during medical school and my postmedical school training, the most dynamic professors I encountered were rheumatologists. They were deeply interested in the diseases they treated and very passionate about their work. Their enthusiasm was contagious, and I found myself drawn to the field because of them.
significant progress in this area. While we’re not perfect, we’re certainly a long way from where we were in the 1970s and 80s.
Q2You've been instrumental in the development of therapies for rheumatoid arthritis and other rheumatic diseases. What do you see as the most significant advancement in this field over the past decade?
At the time, we had very few effective treatments, and my goal was to contribute to developing therapies that were safer and more effective than gold salts or corticosteroids
The second reason, and perhaps the more important, is personal. My favorite aunt had rheumatoid arthritis. She was treated in the 1950s, 60s, and 70s with steroids and gold salts, which were the standard therapies at the time. Unfortunately, her disease progressed to the point where she ended up in a wheelchair, and she passed away in her early 50s, likely due to complications from both the disease and the steroids. That personal connection drove my interest in a pursuit of a fellowship in rheumatology.
During my fellowship, I was trained in clinical trials, which aligned with my goal of finding better medications. At the time, we had very few effective treatments, and my goal was to contribute to developing therapies that were safer and more effective than gold salts or corticosteroids. Over the past 40 years, we’ve made
That’s an interesting question, and it takes us quite a long way back. When I started practicing, the main treatments for rheumatoid arthritis were gold salts, steroids, and nonsteroidal anti-inflammatory drugs. These were often toxic and not particularly effective.
I finished my training in 1974 and started practicing in 1975. In 1977, I attended an American College of Rheumatology (ACR) meeting in Boston, where a former co-fellow introduced me to methotrexate. At the time, it was being used offlabel, about 10–12 years before it was FDA-approved for rheumatoid arthritis. By 1980, I had most of my patients on methotrexate, and somewhere between 15–25 mg of folic acid a week, and the results were significantly better. That was one major advancement.
Then, in the early 1990s, I was approached to work on trials for TNF inhibitors, starting with etanercept. These drugs were a game-changer, far more effective than methotrexate alone. From there, I became involved with other biologics, all of which were excellent but not perfect.
In the late 2000s, we started seeing the introduction of JAK inhibitors, which I believe are somewhat more efficacious than biologics, though they come with safety considerations. Most recently, CAR-T cell therapies have shown dramatic results, although they’re still in the early stages and very expensive.
So, over the years, we’ve gone from having almost no effective treatments to a wide range of options that significantly improve patient outcomes.
Q3Could you share with us some of the key findings from the SELECT-BEYOND study, particularly regarding the long-term efficacy and safety of upadacitinib in patients with rheumatoid arthritis?
There are two key studies involving upadacitinib that I think are noteworthy: SELECTBEYOND and SELECT-COMPARE. Let’s start with SELECT-BEYOND, which involved patients who had failed biologics and were subsequently treated with JAK inhibitors like upadacitinib. The
study demonstrated that these patients could respond well to JAK inhibitors, which was a significant finding.
However, I believe SELECTCOMPARE is the more impactful study. In this trial, we directly compared the efficacy and safety of upadacitinib, a JAK inhibitor, with adalimumab, which is probably the most widely used TNF inhibitor worldwide. The trial showed that upadacitinib was actually more efficacious than adalimumab.
This finding is particularly important because it challenges the traditional treatment paradigm. Typically, after methotrexate failure, clinicians turn to TNF inhibitors as the next step. However, the SELECT-COMPARE results suggest that, in an ideal world where cost and access aren’t barriers, upadacitinib might be the better option for patients who don’t respond to methotrexate.
Of course, it’s not a perfect world. Factors like cost and safety profiles play a significant role in clinical decision-making. While the efficacy of JAK inhibitors
like upadacitinib is promising, safety concerns, such as cardiovascular risks and venous thromboembolism, must be considered, especially in patients with preexisting risk factors.
One of the key takeaways from the trial and subsequent analyses, including comparisons with findings from the ORAL Surveillance trial, is that patient selection is critical. For example, patients without significant cardiovascular or venous thromboembolism risk factors tend to do well on JAK inhibitors, while those with these risks require careful monitoring and mitigation strategies, regardless of the therapy used.
In practice, SELECT-COMPARE highlights the potential of JAK inhibitors as first-line treatments after methotrexate failure. It also reinforces the importance of tailoring treatments to individual patients’ risk profiles to optimize outcomes while minimizing safety concerns.
Q4 What factors do you think are most critical in determining whether a patient responds well to targeted therapies such as JAK inhibitors?
That’s a really great question, one we don’t have an answer for yet. Two major unmet needs in rheumatology are predicting who will respond to which therapy safely and treating the patients who don’t respond to any available therapy.
Right now, we don’t have reliable tests or predictors to determine the best medication for a new patient. It’s trial and error, which can be frustrating for both clinicians and patients. This is an area where AI might help in the future by analyzing vast amounts of data to identify patterns and predictors of response.
Q5
How do you see technologies like AI and machine learning influencing rheumatology research and practice in the coming years?
AI is an exciting but challenging tool. One of the risks is ‘garbage in, garbage out’: if the data fed into AI models isn’t robust, the results won’t be reliable. That said, AI has the potential to analyze complex datasets that even the smartest human minds can’t process entirely.
For example, AI could help identify which patients are likely to respond to specific therapies or uncover new mechanisms of action for drug development. However, we need to approach it cautiously to ensure the outputs are meaningful and actionable.
Q6 What are the biggest challenges in bringing new therapies from research to clinical pra ctice, and how do you think these can be addressed?
The challenges are multifaceted. First, the development pipeline itself is incredibly demanding. It begins with preclinical experiments, which are conducted in test tubes and animal models, typically rodents. These models are meant for understanding whether a particular mechanism might work, but they are not perfect, as rodents are not people.
Of the thousands of compounds tested preclinically, only a small fraction, maybe 10%, make it to Phase I clinical trials, and even less progress to Phase II. By Phase III, where safety and efficacy are rigorously evaluated, perhaps 1% of the original compounds remain. That is an enormous drop-off.
This is where AI could help by analyzing preclinical data and
One of the risks is ‘garbage in, garbage out’: if the data fed into AI models isn’t robust, the results won’t be reliable
narrowing the field. Instead of starting with 1,000 compounds, you might start with 50 that are more likely to succeed, reducing costs and increasing efficiency.
Another challenge is running clinical trials. Finding the right patients has become increasingly difficult, especially for diseases like rheumatoid arthritis. When I started trials in the 1990s, it was relatively easy to enroll patients because we had so few effective therapies. Now, with 16 approved medications, many of which are available as generics or biosimilars, it is harder to find patients who meet the ethical and clinical criteria for participating in trials. If you cannot find patients, you cannot conduct trials, and if you cannot conduct trials, you cannot bring new therapies to market.
There is also the challenge of designing trials. Protocols must be written carefully to answer a
single, clear question about a drug’s effectiveness and safety. However, some protocols try to answer too many questions, which can dilute the results and make it harder to draw conclusions.
Finally, there is the issue of regulatory approval and cost. Even when a drug shows promise, the expense of developing it, often upwards of a billion dollars, makes pharmaceutical companies cautious, especially when competing against wellestablished therapies.
Addressing these challenges requires better trial designs, innovative technologies like AI, and possibly new regulatory approaches to streamline the process. But at the end of the day, the biggest challenge is finding ways to ethically and efficiently test therapies while ensuring they meet the highest standards of safety and efficacy.
Q7Are there any emerging drugs or therapeutic approaches that you believe hold promise?
Yes, there are several interesting developments on the horizon. At the recent ACR meeting, there was a report on an anti-CD40 ligand, which showed promising results. Another area generating
interest is vagus nerve stimulation, a device-based therapy. While it didn’t show very dramatic efficacy, it could be an option for patients who, for some reason, cannot or will not take biologics or injectable therapies or for patients who have failed all approved therapies. Thus, this might fill a niche for some patients. There are also ongoing trials with programmed cell death protein 1 (PD-1) antagonists and CD40 inhibitors, as well as new JAK inhibitors.
The most exciting area, in my opinion, involves CAR-T cell therapy and T cell engagers. These are highly sophisticated and expensive treatments, but the results so far have been dramatic, particularly for patients who haven’t responded to many other therapies. It’s likely that these therapies will become increasingly important, although their complexity and cost remain significant hurdles.
Another challenge is finding pharmaceutical companies willing to invest the enormous resources, often over a billion dollars, required to develop new drugs. The bar is very high because we already have many effective therapies. However, there’s still a subset of patients, around 20%, who don’t respond to any current treatment. For them, these emerging approaches could be life-changing.
So, while progress continues, we’re constantly balancing innovation with practicality. It’s crucial to keep pushing for new treatments, especially for those patients who remain unresponsive to existing therapies.
Q8 With emerging treatments, how can clinicians balance the benefits of innovative therapies with potential long-term risks?
This balance should be addressed in clinical trials. Phase III trials should compare new therapies to existing ones, not just placebos, to assess how well they work relative to what’s already available.
For safety, we need long-term prospective studies with large patient populations, similar to the oral surveillance trial. These studies provide critical insights into risks that might not appear in smaller trials.
For clinicians, the key is to stay informed by reading the latest clinical trial data, not just reviews or meta-analyses, and applying those findings to patient care. It’s a challenging but essential part of advancing the field and improving outcomes for patients.
Daniel Wallace
Associate
Director,
Rheumatology Fellowship Program Medicine, Cedars-Sinai, Los Angeles, California, USA
Q1 Your research was among the first to highlight vitamin D dysfunction and the role of IL-6 in lupus. How have these discoveries influenced clinical approaches to managing the disease, and what areas of lupus research do you think hold the most promise for the future?
conducted at community or private practice sites, which limited their scope and quality. LuCIN involves 42 academic centers in the US and Canada, with access to an aggregate of 26,000 patients with lupus. Since its inception, the quality of lupus studies has greatly improved.
It’s not specific just to lupus, but IL-6 is a key cytokine in inflammation
In the late 1980s and early 1990s, we were among the first to suggest that IL-6 played a role in lupus. It’s not specific just to lupus, but IL-6 is a key cytokine in inflammation. Our group was the first to demonstrate its significance, which has since been validated. Treatments targeting IL-6 have become available, and these are now part of the therapeutic landscape.
As for vitamin D, this remains an area of unmet need. There’s a split in the literature, with some studies supporting its role in lupus and others not finding a connection. However, the majority of evidence suggests that vitamin D does play a role in lupus, and it probably should be a part of supplements for most lupus patients.
Q2
As part of Lupus Clinical Investigators Network (LuCIN) and Systemic Lupus Erythematosus International Collaborating Clinics (SLICC), what recent studies or trials have you been involved in that you believe will have a significant impact on patient outcomes in lupus or other autoimmune diseases?
One challenge with lupus trials historically was that many were
Recent advancements have been made in areas such as small oral molecules, complement activation inhibitors, cytokine inhibitors, B cell blockers, and T cell blockers. SLICC, on the other hand, started in the early 1990s by tracking approximately 1,400 newly diagnosed patients with lupus. It has now expanded globally, encompassing all six continents, to build a new cohort. This expansion includes developing a new damage index and other metrics to further understand and treat lupus.
Q3 The introduction of biologics has revolutionized care for many rheumatic diseases. What do you see as the next big innovation in treatment?
The next big innovation will involve cellular therapies, small oral molecules, stem cell treatments, and using combination therapies, applying two or three treatments simultaneously instead of just one. These advancements hold significant promise for the future of rheumatology.
Q4
In our previous interview, you mentioned the LuCIN initiative studying the lower rates of COVID-19 among patients with lupus. Have there been any significant developments since your last update?
It turns out that wasn’t the case. Patients with lupus contract COVID-19 at similar rates as the general population, but they tend to have more severe cases. They also experience stronger reactions to vaccines and face a slightly higher incidence of long-term COVID-19 compared to others.
Q5
Your book, 'The Lupus Book', has sold over 100,000 copies since its publication, becoming a vital resource for patients and healthcare professionals alike. What do you think has contributed to its enduring success, and how has it helped shape the conversation around lupus care and education?
Most lupus advocacy organization pamphlets are written at a secondary school level, while medical textbooks are often too
complex for patients. The Lupus Book bridges that gap. It’s written for readers with at least a year of college education or for allied health professionals. It fills a niche for people who want accessible information that is not oversimplified or difficult to understand.
Q6
The Wallace Rheumatic Diseases Foundation has been instrumental in providing free rheumatologic outpatient care to uninsured and underinsured patients. Could you share some of the most significant impacts the foundation has had on patient care and research in rheumatology?
The foundation’s work has been largely centered in Southern California, USA, where I live. We operate a lupus clinic 2 days a week at Cedars-Sinai Medical Center. Additionally, we collaborate with Lupus LA, which offers social work support, fellowships, and grants to patients. These grants help cover essential expenses like utility bills, enabling patients to maintain stability. Over the past 20 years, we’ve helped close to 1,000 patients.
Has the foundation faced any challenges in delivering these services?
Fortunately, we’ve had excellent philanthropic donors, and I believe we’ve made a meaningful difference in the lives of our patients.
Q7
Lastly, looking into the future, what excites you most about the future of rheumatology, and what do you hope to see achieved in the next decade for both patients and the field as a whole?
Biomarkers and AI are paving the way for precision medicine. With these tools, we can identify patients with specific markers that predict their response to particular treatments. This approach will allow us to tailor therapies more effectively, leading to better outcomes for lupus and other rheumatic diseases.
Current Applications and Future Roles of AI in Rheumatology
Author: *Antoni Chan1,2
1. University Department of Rheumatology, Royal Berkshire NHS Foundation Trust, Reading, UK
2. Business Informatics, Systems and Accounting, Henley Business School, University of Reading, UK *Correspondence to antoni.chan@nhs.net
Disclosure: The author declared no conflict of interest.
AI is the process of simulation of human intelligence by computer systems. These processes encompass learning, reasoning, and self-correction by machines. Just like the way the human mind learns, in AI, the machine learns through training using algorithms. After the increased use of AI in various fields such as commerce, finance, and hospitality, it has now made its entry into healthcare in a rapid way. AI has emerged as both a current and future tool that brings the promise of finding solutions to the challenges faced in healthcare.1
AI Technologies
AI technologies include machine learning (ML), deep learning, natural language processing (NLP), image recognition, and large language models (LLM). ML algorithms can analyze vast datasets to identify patterns and predict outcomes. NLP facilitates the extraction from unstructured clinical notes and turns
it into meaningful information. LLMs are AI systems capable of understanding and analyzing large amounts of texts by mimicking human intelligence. LLMs have been increasingly used more recently with access to Generative Pre-trained Transformer (Chat-GPT, San Francisco, California, USA). The terms and domains used in AI systems are shown in Table 1
AI in Rheumatology
AI has been used in various conditions in rheumatology. This includes rheumatoid arthritis (RA), axial spondyloarthritis (axSpA), osteoarthritis, systemic lupus erythematosus, systemic sclerosis, and many others. These conditions often present complex diagnostic and treatment challenges. AI has a role in enhancing the understanding of disease, improving accuracy of diagnosis and treatment of rheumatic conditions, as well as enhancing research. The evaluation of AI includes the assessment of its strengths, weaknesses, challenges, and opportunities.
ML
DL
USL
A subset of AI that uses algorithms to analyze vast datasets to identify patterns and predict outcomes.
A subset of ML and combines ML processes in a layered structure of artificial neural networks.
A subset of ML that uses models that emulate the brain’s structure and function.
ML method where the algorithm is trained on labeled data.
ML method where the algorithm finds new patterns (clusters) from unlabeled data.
A system that enables the extraction of meaningful information from unstructured clinical notes.
AI systems that use NLPs to analyze and understand a large amount of text data by mimicking human intelligence.
DL: deep learning; LLM: large language models; ML: machine learning; NLP: natural language processing; NN: neural networks; SL: supervised learning; USL: unsupervised learning.
STRENGTHS OF AI
With the increasing amount of data being recorded on electronic health records (EHR) and health apps in hospitals and primary care settings, there is a need to harness this information to improve the care of patients. ML algorithms can analyze large datasets from EHRs and health registries.1 This allows it to identify patterns and predict outcomes in patients. ML models, for instance, have been used to predict disease activity in RA by analyzing clinical data and biomarkers.2 The predictive capability of ML allows for personalized treatment plans and, in essence, should enhance shared decision-making between patients and healthcare providers as more options are discussed. The use of AI goes beyond objective data as LLMs can also analyze subjective datasets. For example, LLM-driven sentiment analysis has been used for more subjective patient reported outcomes in fibromyalgia.3 This can facilitate diagnosis of fibromyalgia that can be challenging, such as in primary care with shorter appointment times. This
LLM-driven approach can detect subtle differences in pain and nuances in patient reported symptoms, aiding the diagnosis of fibromyalgia. AI algorithms can also process and analyze data faster and possibly more accurately than human clinicians. This in the long term will improve patient outcomes.
NLP facilitates the extraction of meaningful information from unstructured clinical notes. It streamlines the information from the patient’s history and referral, which aids in more accurate diagnoses and treatment plans. By analyzing EHRs, NLP can enhance the understanding of disease patterns and treatment responses. Early detection of rheumatic diseases is critical for effective management.
Convoluted neural networks are used for image recognition, such as for radiological images. With the increased demand for imaging in radiology, scans may take much longer for reporting by the radiologist. AIpowered image recognition systems can assist in the interpretation of X-ray and MRI images,
Table 1: Terms and domains in AI.
NN
SL
NLP
LLM
Prediction of risk of developing disease2,3
Early diagnosis through triage of referrals6
AI-based symptom checker to facilitate diagnosis2,6
Disease classification7,8
Identification of clusters and phenotypes with similarities7,8
Analysis of genetic and other biomarkers7,8
Personalized prediction of disease activity including flares7,8
Personalized prediction of treatment response2,9
Personalized prediction of future outcomes2,9
Remote monitoring of patient reported outcomes, wearables, and digital biomarkers7,8
Image recognition and radiomics4,5
identifying joint damage or inflammation with high accuracy. Deep learning has been used to detect inflammatory or structural changes in the sacroiliac joints indicative of axSpA.4 Radiomics is another expanding field that uses AI in imaging. In radiomics, AI systems are used to convert images into high-dimensional, quantifiable data. This is being used, for example, to study prognostic and molecular differences in interstitial lung disease in systemic sclerosis.5 AI systems can reduce the burden on radiologists and improve diagnostic efficiency. AI can also reduce the administrative burden on healthcare providers, allowing them to focus more on patient care. AI can facilitate large-scale analyses of clinical data, enabling researchers to uncover new insights in the pathophysiology of rheumatic diseases and identify novel therapeutic targets. The strengths of AI can be leveraged in the patient pathway at the diagnosis, disease classification, treatment, and monitoring phases. The usage of AI in rheumatology is shown in Table 2
Diagnosis
Early diagnosis can improve long-term outcomes in rheumatic diseases. AI algorithms can analyze data from various sources, including genetic, clinical, and imaging data. The use of EHRs allows the collection of real-world data, including referral information, which can be used to train and validate AI algorithms to predict the probability of inflammatory arthritis such as RA.6
Disease Classification
AI can perform both supervised and unsupervised learning. In supervised learning, the machine learning model is trained based on labeled data. In unsupervised learning, the reverse is done where the machine learning model is trained on unlabeled data. The latter is used to process large databases such as the EHR. This can result in the identification of clusters of patients with similar characteristics or phenotypes. This can improve disease classification.
Table 2: The use of AI in rheumatology.
Treatment Optimization
AI can help tailor treatments to individual patients based on their unique, personalized characteristics. For example, AI has been used to predict giant cell arteritis (GCA) relapse after glucocorticoid (GC) tapering.9 This can aid the clinician in making decisions to taper the GCs slower or increase monitoring in this group of patients with GCA. In RA, deep learning can identify patient clusters that may have different responses to biologic and targeted synthetic diseasemodifying antirheumatic drugs.7 By analyzing treatment responses from large patient cohorts, AI can identify which therapies are more effective for specific patient profiles, thereby improving treatment outcomes and minimizing adverse effects.
Patient Monitoring
AI has been used to enhance remote monitoring. As patients are increasingly seen at different time points in clinics based on their disease activity, the data that is provided in between clinic visits can help monitor and predict outcomes. In RA, an adaptive recurrent neural network has been used to predict active disease using the disease activity 28 joint score and blood sedimentation rate (DAS28-BSR) >2.6 in future appointments.8 Post-COVID-19, with the rise in telemedicine, AI has been used in areas such as wearables. These devices equipped with AI can track symptoms and disease activity in real-time, providing healthcare professionals with valuable data to adjust treatment plans promptly.
WEAKNESSES OF AI
Despite its potential to provide rapid insight, the use of AI has its flaws, weaknesses, and shortfalls. AI systems require high-quality, diverse datasets for effective training. The heterogeneity of data sources and patient populations in rheumatology can hinder the development of robustness. Many AI algorithms, such as deep learning models, operate like black boxes, which makes it
difficult for clinicians to understand how decisions are made. The AI systems can produce inaccurate and unreal contents, which is known as hallucinations. Clinicians work through problem-solving and refinement of decision-making. The lack of transparency in AI can pose a challenge in clinics where trust and accountability are crucial pillars of good medical practice. The use of AI also raises ethical questions regarding patient data security, privacy, and potential biases in algorithm training. As the system uses large and very diverse content for training, it can be prone to creating biased content. Protecting patient information is key for its successful use. AI systems require large datasets that may include sensitive health information. There is a need to ensure equitable access to AI technologies and address biases in algorithms to avoid exacerbating health disparities. A balance between preciseness and explainability is fundamental for AI. Strategies should be developed to ensure equitable access to AI-driven healthcare solutions, especially in areas of high deprivation. There is also a need to ensure robust data encryption, secure storage, and compliance with regulations that safeguard patient privacy.
CHALLENGES FROM AI
Implementing AI in healthcare, including rheumatology, has ethical and safety challenges. Patients should be made aware of how their data is used, and informed consent must be obtained, particularly if it is being utilized for training AI algorithms. Informed consent must clearly communicate the purpose, potential risks, and benefits of data usage. Determining who is responsible for the decisions made by AI systems is a complex issue of accountability and liability. Clear guidelines are needed to establish accountability in cases of clinical errors, misdiagnosis, or adverse outcomes resulting from AI recommendations. AI may change the dynamics of the healthcare provider and patient relationship. The interaction, communication, and personal connection
between both patient and provider need to be enhanced and not diminished with AI.
An ethical dilemma AI poses is the dehumanization of medical actions. Empathy, compassion, and moral subjectivity can only be given by humans to patients. These qualities are essential for clinical care, prevention, and the interaction between a doctor and patient. The use of AI should support rather than replace clinical judgment. There is a risk of a reduction in human critical thinking and reasoning with over-reliance on AI. There are ethical concerns such as AI hallucination and algorithmic bias, which can lead to errors in task management and clinical decision-making.10 On the other hand, AI can enrich various facets of critical thinking when users do not accept AI recommendations without question, analysis, and evaluation of the evidence presented. Healthcare providers should retain the authority to make final decisions regarding patient care. Any output from AI will need human oversight of its use. For this, there must be regulatory frameworks for the use of AI in healthcare. This needs to be continuously monitored and evaluated. Adjustments to AI technologies must meet safety and quality standards. Transparency about how AI systems work and their potential impact on healthcare can improve acceptance by patients and the public. Humans must decide how we use AI ethically, responsibly, and safely.
OPPORTUNITIES FROM AI
Continued efforts are needed to integrate AI into routine clinical workflows. This includes integration of AI within the EHR, interoperability across different software platforms, and interaction with patients through patient portals. Developing userfriendly interfaces that ensure healthcare providers are adequately trained and equipped to use these technologies effectively. Collaborative efforts among rheumatologists, data scientists, and ethicists are essential to address the challenges of AI implementation. Interdisciplinary teamwork
can foster innovation and ensure that ethical considerations are prioritized. There will be a need to include informatics and data management as part of the multidisciplinary team. This collaboration and engagement is necessary to provide oversight of AI systems.
FUTURE PERSPECTIVES
There is a bright future for AI in rheumatology, and this will likely focus on a few key areas. AI-driven tools can be used in personalized treatment strategies by analyzing genomic, imaging, and clinical data. AI can also improve efficiency by automating routine tasks such as monitoring disease activity, interpreting blood and imaging studies, and electronic communication. Virtual care and telemedicine platforms powered by AI can expand access to care. With advances in research, AI technologies are poised to evolve alongside. Future research will emphasize longitudinal studies that assess the long-term safety and impact of AI on patient outcomes in rheumatology. Understanding how AI influences disease progression and treatment response over time will be important to optimize its use.
CONCLUSION
AI presents a transformative opportunity in rheumatology. It offers improved diagnosis and personalized treatment and enhances remote monitoring of patients. While the benefits are substantial, addressing challenges related to data quality, interpretability, and ethical considerations is vital for its successful implementation. AI has the potential to revolutionize the management of rheumatic diseases and pave the way for improved patient care and outcomes. The integration of AI in rheumatology is more than a technological advancement. It represents a paradigm shift in the understanding and treatment of rheumatic conditions. Collaboration and innovation will be essential to harness the full potential of AI in rheumatology.
References
1. Bean DM et al. Hospital-wide natural language processing summarising the health data of 1 million patients. PLOS Digit Health. 2023;2(5):e0000218.
2. Norgeot B et al. Assessment of a deep learning model based on electronic health record data to forecast clinical outcomes in patients with rheumatoid arthritis. JAMA Netw Open. 2019;2(3):e190606.
3. Venerito V, Iannone F. Large language model-driven sentiment analysis for facilitating fibromyalgia diagnosis. RMD Open. 2024;10(2):e004367.
4. Adams LC et al. Artificial intelligence and machine learning in axial spondyloarthritis. Curr Opin Rheumatol. 2024;36(4):267-73.
5. Schniering J et al. Computed tomography-based radiomics decodes prognostic and molecular differences in interstitial lung disease related to systemic sclerosis. Eur Respir J. 2022;59(5):2004503.
6. Wang B et al. Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning. Decis Support Syst. 2023;166:113899.
7. Kalweit M et al. Patient groups in rheumatoid arthritis identified by deep
learning respond differently to biologic or targeted synthetic DMARDs. PLoS Comput Biol. 2023;19(6):e1011073.
8. Kalweit M et al. Personalized prediction of disease activity in patients with rheumatoid arthritis using an adaptive deep neural network. PLoS ONE. 2021;16(6):e0252289.
9. Venerito V et al. Validity of machine learning in predicting giant cell arteritis flare after glucocorticoids tapering. Front Immunol. 2022;13:860877.
10. Zhai C et al. The effects of overreliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learn Environ. 2024;11(1):28.
Steroid-Induced Hyperglycemia in Rheumatoid Arthritis: A Case Report
Background: Steroid-induced hyperglycemia is a common side effect of steroid therapy, such as prednisone, used in the treatment of various conditions, including rheumatoid arthritis. Elevated blood glucose levels characterize this metabolic disturbance (steroid-induced hyperglycemia), which can pose challenges in patient management, particularly in those without prior diabetes history.
Aim: The authors present the case of a 58-year-old female with rheumatoid arthritis who developed hyperglycemia after initiating prednisone therapy. It aimed to illustrate the clinical course, management, and outcomes of steroid-induced hyperglycemia in this patient.
Clinical details: The patient, with a history of rheumatoid arthritis, received a short-term course of prednisone due to worsening symptoms. Within a week, she developed symptoms of hyperglycemia despite no prior history of diabetes. Laboratory tests confirmed elevated blood glucose levels and a glycated hemoglobin of 8.5%. Her blood glucose remained elevated, despite dietary modifications and oral hypoglycemic agents, requiring insulin therapy.
Outcomes: Insulin therapy initiation with a basal-bolus regimen led to gradually recovering blood glucose levels. Regular monitoring and adjustments resulted in stable fasting and postprandial glucose levels within target ranges. The patient reported symptom improvement and increased energy levels.
Conclusion: This case highlights the importance of vigilant monitoring and management of steroid-induced hyperglycemia in patients receiving steroid therapy, even for short durations. Collaborative efforts between rheumatology, endocrinology teams, and clinical pharmacists were crucial in ensuring optimal disease control while minimizing long-term steroid use. Individualized treatment plans and patient education are essential for optimizing outcomes and reducing risks associated with steroid-induced hyperglycemia.
Key Points
1. Steroid-induced hyperglycemia is a frequent side effect of steroid therapy, caused by mechanisms such as insulin resistance and increased hepatic glucose production, and can occur even with short-term steroid use.
2. The case of a 58-year-old female with rheumatoid arthritis illustrates how prednisone led to significant hyperglycemia, requiring insulin therapy after oral hypoglycemic agents were insufficient. Management strategies included close glucose monitoring, dietary modifications, and insulin therapy, with collaborative care from rheumatology, endocrinology, and clinical pharmacy teams.
3. The case highlights the importance of early recognition, patient education, and individualized treatment plans to manage steroid-induced hyperglycemia and minimize long-term steroid use.
BACKGROUND
Steroids are widely used in various medical conditions, including rheumatoid arthritis, asthma, and inflammatory bowel disease. They possess potent anti-inflammatory effects by suppressing the immune system and reducing inflammation. However, one of the significant side effects associated with the use of steroids, such as prednisone, is steroid-induced hyperglycemia.1
Steroid-induced hyperglycemia is a common metabolic disturbance determined by increased blood glucose levels.2 The mechanisms underlying steroid-induced hyperglycemia are multifactorial. Steroids can impair insulin sensitivity and glucose uptake in peripheral tissues, leading to insulin resistance. Additionally, they stimulate hepatic gluconeogenesis, resulting in increased hepatic glucose production. These mechanisms contribute to elevated blood glucose levels in patients receiving steroids, leading to steroid-induced hyperglycemia.3
The incidence of steroid-induced hyperglycemia varies depending on the dose and duration of steroid therapy.
Higher doses and prolonged use of steroids are associated with an increased risk of developing steroid-induced hyperglycemia. However, even short courses of steroids can lead to hyperglycemia.4 Patients
with pre-existing diabetes or glucose intolerance are particularly susceptible to developing steroid-induced hyperglycemia.5
The clinical presentation can vary from asymptomatic to severe hyperglycemia with ketosis or hyperosmolar hyperglycemic state (HHS). HHS is a life-threatening complication of steroid-induced hyperglycemia that requires prompt medical attention.6 The management of steroid-induced hyperglycemia involves close monitoring of blood glucose levels and initiating appropriate treatment strategies.
Monitoring blood glucose levels in patients receiving steroids, particularly those with risk factors for diabetes or glucose intolerance, is crucial in detecting and managing steroidinduced hyperglycemia. Regular monitoring helps in early identification of hyperglycemia and allows for timely intervention to prevent complications. The American Diabetes Association (ADA) recommends frequent blood glucose monitoring, particularly in patients receiving high-dose steroids or those with pre-existing diabetes or glucose intolerance.7
Once diagnosed, the treatment approach may vary depending on the severity of hyperglycemia. In mild cases, dietary modifications and oral hypoglycemic agents can be employed to control blood glucose levels. In moderate-to-severe cases of steroid-induced hyperglycemia,
blood glucose levels are significantly elevated and may not be adequately controlled with dietary modifications and oral hypoglycemic agents alone. Such cases often require more intensive management to achieve glycemic control and prevent complications. According to the ADA Standards of Care (2024), insulin therapy should be considered for patients when glycated hemoglobin (HbA1c) levels exceed 9–10%, or if oral medications are insufficient in controlling blood glucose levels effectively. Insulin becomes necessary in these situations to more precisely manage blood glucose levels and mitigate the risk of complications associated with uncontrolled hyperglycemia.8 Insulin therapy maintains blood glucose levels within a target range to minimize the risk of hypoglycemia. Insulin therapy can be initiated using subcutaneous insulin injections or continuous intravenous insulin infusion. The choice of insulin regimen depends on the individual patient's needs and the clinical setting. In recent years, long-acting insulin analogs, such as insulin glargine, have gained popularity for managing steroid-induced hyperglycemia due to their favorable pharmacokinetic profile.9
The goals of this case report are to illustrate the clinical course, management strategies, and outcomes of steroid-induced hyperglycemia in a patient with rheumatoid arthritis. By presenting this case, the authors aim to highlight the challenges in managing hyperglycemia induced by steroid therapy, even for short durations. Understanding the nuances of such cases is crucial for healthcare providers to develop effective treatment plans tailored to individual patient needs. The importance of these cases lies in their ability to underscore the necessity for vigilant monitoring and individualized management of steroidinduced hyperglycemia. As steroid use is common in treating various conditions, recognizing and addressing hyperglycemia early can significantly impact patient outcomes. Collaborative efforts among rheumatology, endocrinology teams, and clinical pharmacists are essential in ensuring optimal disease control while minimizing
long-term steroid use. These cases provide valuable insights into best practices for managing steroid-induced hyperglycemia and underscore the importance of patient education and interdisciplinary collaboration in achieving favorable outcomes.
CASE REPORT
A 58-year-old female patient with a history of rheumatoid arthritis presented to the Rheumatology Department with complaints of worsening joint pain and swelling. She had been previously diagnosed with rheumatoid arthritis 6 years ago and had been managed with disease-modifying antirheumatic drugs (DMARD) and occasional courses of oral steroids during disease flares. Due to worsening symptoms and evidence of disease activity on clinical examination and laboratory tests, the decision was made to initiate a short-term course of oral prednisone. The patient was started on oral prednisone at a dose of 20 mg/day for two weeks, followed by a tapering dose over the next four weeks. She was advised to continue her regular DMARD therapy during this period. The patient had no history of hypertension, diabetes, or coronary artery disease.
Clinical Course
Within a week of starting prednisone, the patient reported increased thirst, frequent urination, and fatigue. A fingerstick blood glucose test, performed at home, revealed a reading of 220 mg/dL. The patient contacted the department and was advised to come for further evaluation. On examination, the patient appeared fatigued but otherwise stable. Her vital signs were within normal limits. Laboratory investigations revealed a fasting blood glucose level of 240 mg/dL and a glycated HbA1c level of 8.5%. Additional laboratory tests, including renal and liver function tests, were within normal limits. Based on the clinical presentation and laboratory findings, the patient was diagnosed with steroid-induced hyperglycemia.
The decision was made to monitor blood glucose levels closely and initiate dietary modifications with medication adjustments to achieve glycemic control.
Management and Follow-Up
Upon diagnosis of steroid-induced hyperglycemia, the patient was initially managed with dietary modifications and oral hypoglycemic agents. Specifically, she was prescribed metformin 500 mg twice daily and glipizide 5 mg once daily (Table 1). Despite these interventions, her blood glucose levels remained elevated. Given the persistence of hyperglycemia, insulin therapy was initiated when the patient's HbA1c level reached 8.5%. A basal-bolus insulin regimen was chosen, starting with insulin glargine at a dose of 10 units daily for basal coverage and insulin lispro at a dose of 4 units before each meal for prandial control. These doses were adjusted based on regular blood glucose monitoring. Throughout the follow-up period, the patient's blood glucose levels were closely monitored, and her insulin doses were titrated accordingly. Collaborative efforts between the rheumatologist, endocrinologist, and clinical pharmacists were crucial in optimizing her disease control while minimizing the longterm need for steroids. Regular follow-up appointments ensured that the patient's glycemic control was maintained, and her symptoms improved significantly. The patient was advised to follow a balanced diet with a reduced intake of simple carbohydrates and sugary beverages. She was educated about the importance of portion control and regular meal timings. Additionally, she was referred to a registered dietitian for detailed dietary counseling and meal planning. Considering the moderate severity of hyperglycemia and the need for prompt glycemic control, insulin therapy was initiated. The patient was started on a basalbolus insulin regimen using subcutaneous insulin injections. Basal insulin (glargine) was administered once daily at bedtime, while rapid-acting insulin (lispro) was administered before meals based on a carbohydrate-
counting approach. The initial insulin doses were titrated based on the patient's blood glucose levels and self-monitoring.
Regular follow-up appointments were scheduled to monitor the patient's glycemic control and adjust insulin doses as needed. During these visits, blood glucose levels were closely monitored, and adjustments were made to the insulin regimen to achieve optimal glycemic control while minimizing the risk of hypoglycemia. Over several weeks, with close monitoring and appropriate insulin titration, the patient's blood glucose levels gradually improved. Her fasting blood glucose levels stabilized around 100–130 mg/dL, and her postprandial blood glucose levels remained within the target range of 140–180 mg/dL (Table 2). The patient reported improvement in her hyperglycemia symptoms and felt more energetic. During follow-up visits, the patient's overall health status, including her rheumatoid arthritis, was assessed. Adjustments were made to her DMARD therapy to optimize disease control while minimizing the need for long-term steroid use.
DISCUSSION
Steroid-induced hyperglycemia is a wellrecognized side effect of steroid therapy. It occurs due to the complex interplay of multiple mechanisms, including insulin resistance, impaired glucose uptake in peripheral tissues, and increased hepatic glucose production.10-12 The prevalence of steroid-induced hyperglycemia varies depending on factors such as the dose and duration of steroid therapy, as well as individual patient characteristics.12-13
Steroids, like prednisone, possess potent anti-inflammatory properties and are commonly used to treat various medical conditions, including rheumatoid arthritis, asthma, and inflammatory bowel disease.10-11 However, the use of steroids is associated with a wide range of adverse effects, including hyperglycemia. The risk of developing steroid-induced hyperglycemia
Tab. Metformin
500 mg (twice daily)
Tab. Glipizide 5 mg (once daily)
Insulin Glargine 10 units (once daily)
Insulin Lispro 4 units pre-meal
is influenced by several factors, such as the dose and duration of steroid therapy, underlying patient characteristics, and concurrent use of other medications.14-16 The mechanisms underlying steroid-induced hyperglycemia are multifactorial. Steroids can impair insulin sensitivity and glucose uptake in peripheral tissues, leading to insulin resistance. They can also stimulate hepatic gluconeogenesis, which increases hepatic glucose production.11-12 These mechanisms contribute to elevated blood glucose levels in patients receiving steroids, ultimately leading to steroid-induced hyperglycemia. Dietary modifications play a significant role in the management of steroid-induced hyperglycemia. Patients are advised to follow a balanced diet with reduced intake of simple carbohydrates and sugary beverages. Portion control and regular meal timings are emphasized to help stabilize blood glucose levels.
Insulin therapy is often required in moderate-to-severe cases of steroid-induced hyperglycemia to achieve glycemic control.
The choice of insulin regimen depends on individual patient characteristics and the clinical setting. Subcutaneous insulin injections and continuous intravenous insulin infusion are the two main approaches to insulin therapy. In recent years, long-acting insulin analogs, such as insulin glargine, have gained popularity for managing steroid-induced hyperglycemia due to their favorable pharmacokinetic profile.17-18 These analogs provide basal insulin coverage that mimics physiological insulin secretion and helps achieve stable glycemic control.
In this case, the patient developed hyperglycemia after starting a shortterm course of prednisone for rheumatoid arthritis. This highlights the importance of recognizing and managing steroid-induced hyperglycemia in patients receiving steroid therapy, even for a limited duration. The decision to initiate a short-term course of prednisone was based on worsening symptoms and evidence of disease activity. However, the patient's prediabetes history increased the risk of developing steroidinduced hyperglycemia. The patient
Table 1: Medications.
Table 2: Laboratory findings.
had a history of rheumatoid arthritis and had been managed with DMARDs and occasional courses of oral steroids during disease flares. This background information further underscores the relevance of vigilantly monitoring blood glucose levels in patients with pre-existing conditions that increase the risk of hyperglycemia.
Subsequently, the patient developed symptoms of hyperglycemia, including increased thirst, frequent urination, and fatigue. The diagnosis of steroid-induced hyperglycemia was confirmed through blood glucose testing. Prompt recognition of these symptoms and timely diagnosis allowed for early intervention and management. The patient was educated about the importance of dietary modifications and was referred to a registered dietitian for detailed counseling and meal planning. Verbal informed consent was obtained from the patient for this case report. Lifestyle modifications, including diet adjustments, play a crucial role in managing steroid-induced hyperglycemia.
Considering the moderate severity of hyperglycemia, the decision was made to initiate insulin therapy in this case. A basalbolus insulin regimen was chosen to provide
References
1. Bonaventura A, Montecucco F. Steroid-induced hyperglycemia: an underdiagnosed problem or clinical inertia? a narrative review. Diabetes Res Clin Pract. 2018;139:203-20.
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basal insulin coverage and prandial insulin control, enabling a flexible and individualized approach to glycemic management. Close monitoring of blood glucose levels and regular adjustments of the insulin regimen based on the patient's needs and monitoring results were implemented. Throughout the management process, the patient received extensive education about steroid-induced hyperglycemia. This included understanding the importance of blood glucose monitoring, the role of lifestyle modifications, and the use of insulin therapy. Collaborative efforts between the patient’s rheumatologist, endocrinologist, and clinical pharmacists were instrumental in optimizing disease control while minimizing the long-term need for steroid use.
CONCLUSION
In conclusion, this case underscores the need for healthcare professionals to be vigilant in monitoring and managing steroidinduced hyperglycemia in patients receiving steroids. Individualized treatment plans, interdisciplinary collaboration, and patient education are crucial in optimizing outcomes and minimizing the potential risks associated with steroid-induced hyperglycemia.
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