A167: Variations in Patterns of Care Across Pediatric Rheumatic Diseases in the Childhood Arthritis & Rheumatology Alliance Network Registry

• Published in: Arthritis & rheumatology (Hoboken, N.J.) Vol. 66; no. S3; pp. S215 - S216
• Main Authors: Natter, Marc D., Ong, Mei‐Sing, Ilowite, Norman T., Mandl, Kenneth D., Mieszkalski, Kelly L., Sandborg, Christy I., Wallace, Carol, Schanberg, Laura E.
• Format: Journal Article
• Language: English
• Published: 01.03.2014
• ISSN: 2326-5191; 2326-5205
• DOI: 10.1002/art.38593

Background/Purpose: In 2009, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) established a longitudinal multi‐center, multiple disease U.S. national registry (CARRA Registry) for pediatric rheumatology with the intent of providing a new framework to drive observational clinical research and best practices, evidence‐based care. Simultaneously, recognizing that widely variable therapeutic approaches hinder the ability to conduct meaningful comparative effectiveness studies and pragmatic trials in pediatric rheumatic diseases, CARRA investigators convened expert groups to formulate new consensus‐based treatment plans (CTPs) in 5 major pediatric rheumatic disease areas. As the CTP approaches are adopted, it is important to establish baseline treatment variability across pediatric rheumatic diseases and clinical sites in the CARRA network. Using longitudinal data from the CARRA Registry, we provide a first description of variability of care across the network. Methods: We examine variations of medication usage across 55 clinical sites in the treatment of 8 rheumatic conditions, including juvenile idiopathic arthritis (JIA), SLE and mixed connective tissue disease (MCTD), juvenile dermatomyositis (JDM), localized scleroderma, systemic sclerosis, juvenile primary fibromyalgia syndrome (JPFS), sarcoidosis, and vasculitis. Management of uveitis in JIA patients was also assessed. Study participants include all CARRA registry subjects enrolled in May 2010 through December 2013. Medications were categorized into 4 major classes: biologics, DMARDs, steroids and NSAIDs. We compare the percentage of patients exposed to each medication class at each; care variations were quantified using dispersion measures of standard deviation and range. A subgroup analysis was conducted to assess care variations among the largest group of subjects with similar characteristics of and low disease activity (JIA subjects with an average active joint count of 0 to 1 averaged over the enrolment period), where treatment were hypothesized to be most similar. Results: 8,869 subjects were included in data analysis. Therapeutic approaches were highly variable for all 8 rheumatic diseases (Table 1, Fig 1). Subgroup analysis for JIA showed persistence of variability (Fig 2). Conclusion: We quantify a substantial degree of therapeutic practice variability across sites, persisting across disease‐severity‐matched cohorts. Although enrollment bias is a significant limitation, the magnitude of the variability for the largest cohort (JIA) and persistence across multiple diseases and subtypes supports a widespread effect. This baseline quantification and methods developed for assessing variability will support ongoing efforts to monitor new consensus treatment protocol‐based standardization efforts across the CARRA network.