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Defining criteria for disease activity states in nonsystemic juvenile idiopathic arthritis based on a three-variable juvenile arthritis disease activity score



Defining criteria for disease activity states in nonsystemic juvenile idiopathic arthritis based on a three-variable juvenile arthritis disease activity score



Arthritis Care and Research 66(11): 1703-1709



To determine cutoff values for defining the states of inactive disease (ID), low disease activity (LDA; or minimal disease activity), moderate disease activity (MDA), and high disease activity (HDA) using the clinical (3-variable) Juvenile Arthritis Disease Activity Score (cJADAS). For selection of cutoffs, data from a clinical database including 609 children with juvenile idiopathic arthritis (JIA) were used. Optimal cutoffs were determined against external criteria by calculating the 75th and 90th percentile (for ID and LDA) and 10th and 25th percentile (for HDA) of cumulative score distribution and through receiver operating characteristic curve analysis. External criteria included definitions for ID and LDA cutoffs and therapeutic decisions for HDA cutoffs. MDA cutoffs were set at the score interval in-between LDA and HDA cutoffs. Crossvalidation was performed using 2 JIA patient samples (n = 485) and was based on assessment of construct and discriminant validity. The selected cutoffs were as follows: ≤1 for ID in both oligoarthritis and polyarthritis; ≤1.5 and ≤2.5 for LDA in oligoarthritis and polyarthritis, respectively; 1.51-4 and 2.51-8.5 for MDA in oligoarthritis and polyarthritis, respectively; and >4 and >8.5 for HDA in oligoarthritis and polyarthritis, respectively. In crossvalidation analyses, the cutoffs showed a strong ability to discriminate between disease activity states defined subjectively by physicians and parents, levels of pain, and presence/absence of functional impairment and disease damage. Cutoff values for classifying various disease states in nonsystemic JIA using the cJADAS were developed. The cutoffs revealed good measurement characteristics in crossvalidation analyses and are suited for application in clinical practice and research.

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Accession: 052468594

Download citation: RISBibTeXText

PMID: 24980508

DOI: 10.1002/acr.22393


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