TY - JOUR T1 - Prevention of disease flares by risk-adapted stratification of therapy withdrawal in juvenile idiopathic arthritis: results from the PREVENT-JIA trial JF - Annals of the Rheumatic Diseases JO - Ann Rheum Dis SP - 990 LP - 997 DO - 10.1136/annrheumdis-2021-222029 VL - 81 IS - 7 AU - Joachim Gerss AU - Monika Tedy AU - Ariane Klein AU - Gerd Horneff AU - Maria Miranda-Garcia AU - Christoph Kessel AU - Dirk Holzinger AU - Valda Stanevica AU - Joost F Swart AU - David A Cabral AU - Hermine I Brunner AU - Dirk Foell Y1 - 2022/07/01 UR - http://ard.bmj.com/content/81/7/990.abstract N2 - Objectives To investigate the ability of high-sensitivity C-reactive protein (hsCRP) and S100A12 to serve as predictive biomarkers of successful drug withdrawal in children with clinical remission of juvenile idiopathic arthritis (JIA).Methods This multicentre trial (PREVENT-JIA) enrolled 119 patients with JIA in clinical remission, and 100 patients reached the intervention phase in which the decision whether to continue or stop treatment was based on S100A12 and hsCRP levels. Patients were monitored for 12 months after stopping medication for flares of disease. Results were compared with withdrawal of therapy without biomarker-based stratification in patients from the German Biologika in der Kinderrheumatologie (BiKeR) pharmacovigilance registry.Results In the PREVENT-JIA group, 49 patients had a flare, and 45% of patients stopping medication showed flares within the following 12 months. All patients (n=8) continuing therapy due to permanently elevated S100A12/hsCRP at more than one visit flared during the observation phase. In the BiKeR control group, the total flare rate was 62%, with 60% flaring after stopping medication. The primary outcome, time from therapy withdrawal to first flare (cumulative flare rate after therapy withdrawal), showed a significant difference in favour of the PREVENT-JIA group (p=0.046; HR 0.62, 95% CI 0.38 to 0.99). As additional finding, patients in the PREVENT-JIA trial stopped therapy significantly earlier.Conclusion Biomarker-guided strategies of therapy withdrawal are feasible in clinical practice. This study demonstrates that using predictive markers of subclinical inflammation is a promising tool in the decision-making process of therapy withdrawal, which translates into direct benefit for patients.Trial registration number ISRCTN69963079.Data are available upon reasonable request. ER -