Management strategies for articular flares during biologic therapy in non-systemic polyarticular JIA: a multicentre study
Jonatan Zalcman, Yoel Levinsky, Dana Kenan, Adi Efron, Haran Shani-Narkiss, Irit Tirosh, Amit Ziv, Ruby Haviv, Yonatan Butbul Aviel, Ruth Livny, Gil AmarilyoAbstract
Objectives
Biologic disease-modifying antirheumatic drugs (bDMARDs) are the cornerstone of treatment for juvenile idiopathic arthritis (JIA), yet the optimal management of flares during ongoing biologic therapy remains unclear. We aimed to compare flare-management strategies and identify risk factors for treatment failure in non-systemic polyarticular JIA.
Methods
We conducted a multicentre retrospective cohort study across four tertiary paediatric centres in Israel (01/2008–12/2024). We included children with non-systemic polyarticular JIA phenotypes who achieved clinically inactive disease (CID) on a bDMARD and subsequently experienced an articular flare. Treatment success (TS) was defined as achieving CID within 3 months following intervention and maintaining it for ≥3 months. Multivariable logistic regression and Cox proportional hazards models were used to identify predictors of success and time to remission.
Results
Among 65 patients and 116 flares, five strategies were compared: NSAIDs alone (2.6%), intra-articular corticosteroid injection (IACI; 28.4%), biologic dose optimization (43.1%), IACI plus dose optimization (13.8%), and switching biologics (12.1%). Overall, 71.6% of flares achieved TS. Success rates were highest for IACI (81.8%) and dose optimization (76.0%), and lowest for biologic switching (35.7%). Multivariable analysis identified biologic switching as an independent predictor of lower CID achievement (adjusted OR 0.27; p = 0.036) and significantly delayed remission (HR 0.40; p = 0.006).
Conclusions
In non-systemic polyarticular JIA, local and incremental strategies like IACI and dose optimization result in higher and faster remission rates compared to immediate biologic switching. A stepwise algorithm prioritizing treatment optimization may prevent unnecessary cycling of biologics.