POS0121 GEOGRAPHIC RECRUITING PATTERNS ARE ASSOCIATED WITH PLACEBO RESPONSE RATES IN RHEUMATOID ARTHRITIS CLINICAL TRIALS
Authors: A. Kerschbaumer, M. Steiner, P. Pruckner, J. S. Smolen, D. Aletaha
Journal: Annals of the Rheumatic Diseases (2024)

<h3>Background:</h3> Therapeutic advances of the recent past have led to significant changes in clinical practice when treating patients with rheumatoid arthritis (RA). Since the advent of biological disease modifying anti-rheumatic drugs (DMARD), double-blind randomized controlled trials (RCT) have been the mainstay of drug development. Over time, a significant increase in placebo response rates has been observed in these trials. We hypothesized that one element contributing to these increasing placebo responses are changing recruitment patterns with an increasing move towards geographic areas with less affluent health care systems. <h3>Objectives:</h3> To determine the contribution of changes in geographic recruiting patterns to placebo response rates in RA. <h3>Methods:</h3> We analysed the placebo arms of all available trials with reports on ACR response rates at week 12 and/or week 24. To ensure completeness of trial acquisition, we identified all placebo controlled RCTs investigating biological or targeted synthetic DMARDs in RA patients with established csDMARD background therapy through a systematic literature search covering the time from database inception until December 2nd, 2021. To assess geographic distribution, we extracted the numbers of recruiting centres per country from the original articles or from clinicaltrials.gov. We then used data published from the world bank on the per capita gross national product (GNP) of each recruiting country to calculate a weighted GNP per study, calculated as: weighted GNP=sum[(number of centres per country)*(GNP of respective country at study start)]/(total number of centres of that study). We performed linear mixed model regression with a random effect on study level (to control for study heterogeneity), weighted by the number of patients per study, and adjusted for the global trend of rising GNPs over time. Statistics were conducted using R (version 4.3.1). <h3>Results:</h3> For complete trial evaluation, two independent researchers screened in total 12.793 articles, of which 522 were assessed in detail, with 122 articles finally fulfilling the criteria for trial analysis. Of the included studies the year of study start ranged from 1994 to 2019. All studies had low risk of bias using the version 2 of the Cochrane risk-of-bias tool for randomized trials. A significant positive association of placebo response rates with the study start year was found (estimate: 0.95; SE: 0.21; p&lt;0.001). Recruitment areas have expanded from initially covering only North America and Western Europe to an increasing global recruitment over time (Figure 1), with more recent studies being conducted in less affluent countries. We identified a strong and significant negative association of the weighted and normalised GNP per study and placebo response rates in a study, with an estimate of -3.81% ACR20 response (SE 1.07; p&lt;0.001; Figure 2) per 10.000 international Dollar. <h3>Conclusion:</h3> Placebo response rates are rising over time, in parallel to the change of geographic recruiting patterns, with more recent RCTs recruiting increasingly in less effluent countries. Our data support the hypothesis that these geographic recruitment changes are a significant contributor to the higher placebo rates observed in more recent clinical trials. One explanation may be the more limited access to health care and innovative therapies in less affluent countries, leading to preferential incentives for inclusion in clinical trials and subsequently also higher regression to the mean, which will be considered as placebo response. These effects should have implications for sponsors, investigators, patients, health care providers and political stakeholders. <h3>REFERENCES:</h3> <b>NIL.</b> <h3>Acknowledgements:</h3> We thank the expert librarians, Mag.a Brigitte Wildner and Dr. Eva Chwala, for their assistance with the database searches. The authors also thank B. Bierbaumer, MSc for his assistance in building the underlying database for this project. <h3>Disclosure of Interests:</h3> Andreas Kerschbaumer AbbVie, Amgen, Galapagos, Janssen, Eli Lilly, MSD, Novartis, Pfizer and UCB, AbbVie, Amgen, Galapagos, Janssen, Eli Lilly, MSD, Novartis, Pfizer and UCB, Marlene Steiner: None declared, Pascale Pruckner: None declared, Josef S. Smolen Samsung, Lilly, R-Pharma, Chugai, MSD Janssen, Novartis-Sandoz, Abbvie, Galapagos/Gilead, Novartis-Sandoz, BMS, Samsung, Sanofi, Chugai, R-Pharma, Lilly, Astra-Zeneca, Abbvie, Astra-Zeneca, Lilly, Galapagos, Daniel Aletaha Abbvie, Gilead, Janssen, Lilly, Merck, Novartis, Sanofi, Galapagos, Lilly.