Attitudes and Approaches for Withdrawing Drugs for Children with Clinically Inactive Nonsystemic JIA: A Survey of the Childhood Arthritis and Rheumatology Research Alliance

Objective. To assess the attitudes and strategies of pediatric rheumatology clinicians toward withdrawing medications for children with clinically inactive juvenile idiopathic arthritis (JIA). Methods. Members of the Childhood Arthritis and Rheumatology Research Alliance (CARRA) completed an anonymous electronic survey on decision making and approaches for withdrawing medications for inactive nonsystemic JIA. Data were analyzed using descriptive statistics. Results. Of 388 clinicians in CARRA, 124 completed surveys (32%), predominantly attending pediatric rheumatologists. The most highly ranked factors in decision making for withdrawing medications were the duration of clinical inactivity, drug toxicity, duration of prior activity, patient/ family preferences, joint damage, and JIA category. Diagnoses of rheumatoid factor-positive polyarthritis and persistent oligoarthritis made respondents less likely and more likely, respectively, to withdraw JIA medications. Three-quarters of respondents waited for 6-12 months of inactive disease before stopping methotrexate (MTX) or biologics, but preferences varied. There was also considerable variability in the strategies used to reduce, taper, or stop medications for clinically inactive JIA; most commonly, clinicians reported slow medication tapers lasting at least 2 months. For children receiving combination MTX-biologic therapy, 63% of respondents preferred stopping MTX first. Most clinicians reported using imaging only seldom or sometimes to guide decision making, but most were also reluctant to withdraw medications in the presence of asymptomatic imaging abnormalities suggestive of subclinical inflammation. Conclusion. Considerable variability exists among pediatric rheumatology clinicians regarding when and how to withdraw medications for children with clinically inactive JIA. More research is needed to identify the most effective approaches to withdraw medications and predictors of outcomes.