POS0254 PREDICTING SUCCESSFUL TAPERING OF BIOLOGICS IN PATIENTS WITH INFLAMMATORY ARTHRITIS: SECONDARY ANALYSES FROM THE BIODOPT TRIAL

Abstract

Background: Identification of predictors for successful tapering of biologics in patients with inflammatory arthritis (IA) can help to guide physicians and patients; but, evidence is lacking. Objectives: To identify possible predictors for successful tapering of biological disease modifying anti‐rheumatic drugs (bDMARDs) from baseline characteristics. Methods: BIODOPT was a randomised, open‐label, equivalence trial (EudraCT 2017‐001970‐41) where adults with rheumatoid arthritis (RA; n=61), psoriatic arthritis (PsA; n=26), or axial spondyloarthritis (axSpA; n=55) in ≥12 months low disease activity (LDA) were randomised 2:1 to disease activity‐guided tapering or to continuation of biologics as usual care. Successful tapering at 18 months was pre‐defined as patients who could reduce their biologic dose ≥50% while still being in LDA. Modified poisson regression with robust variance estimator was used for the analyses. Univariable analyses were: tapering group, sex, age, education, tobacco use, body mass index, comorbidity, arthritis characteristics i.e., diagnosis, duration, duration from diagnosis to treatment start, on ≥2 conventional synthetic DMARDs, on methotrexate, on tumour necrosis factor inhibitor (TNFi), on first bDMARD, on bDMARD number ≥3, duration of bDMARD, duration of remission on bDMARD, duration of LDA on bDMARD, previous bDMARD tapering, C‐reactive protein (CRP) before first bDMARD, Health Assessment Questionnaire Disability Index (HAQ‐DI), Pain Visual Analog Scale (VAS), Fatigue VAS, Patient Global Health VAS, Short Form Health Survey 36 (SF‐36) physical and mental component summary (PCS and MCS), tender joints, Physician Global Health VAS, CRP, and in remission. Potentially important variables (univariate p<0.10) were included in the multivariable model. C‐statistics was used to assess model prediction. Results: One‐hundred‐and‐forty‐two patients were randomised to tapering (n=95) or control (n=47) of which 32% (30/95) and 2% (1/47) achieved successful bDMARD tapering at 18 months. A statistically significant associations (univariate p<0.10) was identified between successful tapering and tapering group, HAQ‐DI, Pain VAS, Fatigue VAS, Patient Global Health VAS, SF‐36 PCS, and SF‐36 MCS, Table 1. However, the only independent predictor for achieving successful tapering in the multivariable model was allocation to the tapering group, risk ratio (RR): 14.0 (95%CI: 1.9‐101.3). Interestingly, individuals with a better mental health state (higher SF‐36 MCS) were potentially more likely to achieve successful tapering; RR: 1.06 (95%CI: 0.99‐1.13). A sensitivity analysis only including tapering group and SF‐36 MCS found both variables to be independent predictors, tapering group: RR 14.3 (95%CI: 2.0‐101.9) and SF‐36 MCS: RR: 1.06 (95%CI: 1.01‐1.11). The multivariable model gave reasonable prediction, Figure 1. Conclusion: One‐third of patients with IA achieved successful tapering when the bDMARD dosing interval was spaced after a disease activity‐guided tapering algorithm. The choice of initiating tapering (allocation to tapering) was the only independent predictor; therefore, physicians should keep the option in mind when patients are in sustained LDA. Moreover, better baseline mental health seemed to have potential importance which points to the value of patient comprehension and willingness to engage in the tapering approach.