Published in

BMJ Publishing Group, Annals of the Rheumatic Diseases, p. ard-2023-224742, 2023

DOI: 10.1136/ard-2023-224742

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Definition of rheumatoid arthritis flare based on SDAI and CDAI

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

ObjectiveTo develop and validate definitions for disease flares in rheumatoid arthritis (RA) based on the quantitative Simplified and Clinical Disease Activity Indices (SDAI, CDAI).MethodsWe analysed RA treatment courses from the Norwegian disease-modifying antirheumatic drug registry (NOR-DMARD) and the Vienna RA cohort. In a receiver operating curve analysis, we determined flare definitions for absolute changes in SDAI and CDAI based on a semiquantitative patient anchor. NOR-DMARD was sampled into an 80%-training cohort for cut point derivation and a 20%-test cohort for internal validation. The definitions were then externally validated in the independent Vienna RA cohort and tested regarding their performance on longitudinal, content, face, and construct validity.ResultsWe analysed 4256 treatment courses from NOR-DMARD and 2557 from the Vienna RA cohort. The preliminary definitions for absolute changes in SDAI and CDAI for flare are an increase of 4.7 and 4.5, respectively. The definitions performed well in the test and external validation cohorts, and showed clinical face and construct validity, as flares significantly impact both functional (∆Health Assessment Questionnaire flare vs no-flare +0.43; p<0.001) and structural (∆modified Sharp Score 43% higher after flare; p<0.001) disease outcomes, and reflect consistent worsening across all disease core sets, both patient reported and objective.ConclusionWe here provide novel definitions for flare in RA based on SDAI and CDAI, validated in two large independent real-world cohorts. In times of highly effective medications for RA, and consideration of their tapering, these definitions will be useful for guiding decision making in clinical practice and designing clinical trials.