OP0312 VARIABILITY IN BIOLOGIC PRESCRIPTION PATTERNS FOR RHEUMATOID ARTHRITIS PATIENTS IN THE AMERICAN COLLEGE OF RHEUMATOLOGY INFORMATICS SYSTEM FOR EFFECTIVENESS (RISE) REGISTRY

Background Biologics account for a substantial portion of drug spending in rheumatoid arthritis (RA). Variability in the U.S. in biologic prescribing patterns (and therefore variability in cost of care), and factors that correlate with that variability, remain largely undefined. Objectives We used data from the RISE registry to perform a cross-sectional analysis among U.S. rheumatologists of prescription patterns for biologic DMARDs and tofacitinib and their relationship to RA disease activity. Methods RISE is a U.S. registry that passively collects data on all patients seen by participating practices, thereby reducing selection bias present in single-insurer claims databases. As of December 2017, RISE held validated data from 1.257 providers in 236 practices, representing an estimated 25% of the U.S. clinical rheumatology workforce. We identified patients with available demographic and disease activity information who were assigned ≥2 codes for RA ≥30 days apart between January and December 2017. Practices with 1 of these drugs were assigned to the first drug prescribed and therefore counted only once. We used a hierarchical linear model to predict the probability of receiving a prescription for a biologic based on the patient’s most recent disease activity score (moderate or high disease activity vs. low disease activity or remission) and age from 2016, accounting for clustering by practice. Results We analyzed 53.850 patients from 104 practices. Overall, 29% of patients were prescribed a biologic DMARD or tofacitinib in 2017. TNF inhibitors were most commonly prescribed, followed by abatacept (4.5% of patients), tofacitinib (4.2%), tocilizumab (3.4%), and rituximab (2.5%). We found significant variation within practices in the proportion of patients prescribed any of these drugs (range 0%-100%). In the adjusted analysis, we found that patients with higher disease activity in 2016 were more likely to receive biologics in 2017 (OR 1.56, 95% CI (1.51, 1.62)). Within a practice, as shown in the figure, the risk-adjusted likelihood of receiving a biologic prescription still showed significant variation (between 0%-83% of patients in each practice received a biologic; model c-statistic 0.61). Conclusion In this large sample of U.S. rheumatology practices, higher RA disease activity correlated with the likelihood that a patient would receive a prescription for a biologic, but did not account for all of the variability in biologic prescription patterns. These results suggest that there may be other factors in addition to RA disease activity that account for practice-to-practice variability in biologic prescription patterns. Disclaimer: These data were collected from the ACR’s RISE Registry; however, the views expressed represent those of the authors, not necessarily those of the ACR. Disclosure of Interests Douglas White Grant/research support from: Abbott 2006-2009, Pfizer 2017-2019 (unrelated to this work), Consultant for: Crescendo advisory board 2013-2014, Employee of: Genomyx (Genentech) 1991, Speakers bureau: None since 2008, Michael Evans: None declared, Tracy Johansson: None declared, Rachel Myslinski: None declared, Jinoos Yazdany Grant/research support from: Pfizer, Consultant for: AstraZeneca, Gabriela Schmajuk Grant/research support from: Investigator initiated award from Pfizer from 2015-2018, unrelated to this work