Identifying flares in rheumatoid arthritis: Reliability and construct validation of the OMERACT RA Flare Core Domain Set

Abstract

Objective: To evaluate the reliability of concurrent flare identification using 3 methods (patient, rheumatologist and Disease Activity Score (DAS)28 criteria), and construct validity of candidate items representing the Outcome Measures in Rheumatology Clinical Trials (OMERACT) RA Flare Core Domain Set. Methods: Candidate flare questions and legacy measures were administered at consecutive visits to Canadian Early Arthritis Cohort (CATCH) patients between November 2011 and November 2014. The American College of Rheumatology (ACR) core set indicators were recorded. Concordance to identify flares was assessed using the agreement coefficient. Construct validity of flare questions was examined: convergent (Spearman's r); discriminant (mean differences between flaring/non-flaring patients); and consequential (proportions with prior treatment reductions and intended therapeutic change postflare). Results: The 849 patients were 75% female, 81% white, 42% were in remission/low disease activity (R/LDA), and 16-32% were flaring at the second visit. Agreement of flare status was low-strong (κ's 0.17-0.88) and inversely related to RA disease activity level. Flare domains correlated highly (r's≥0.70) with each other, patient global (r's≥0.66) and corresponding measures (r's 0.49-0.92); and moderately highly with MD and patient-reported joint counts (r's 0.29-0.62). When MD/patients agreed the patient was flaring, mean flare domain between-group differences were 2.1-3.0; 36% had treatment reductions prior to flare, with escalation planned in 61%. Conclusions: Flares are common in rheumatoid arthritis (RA) and are often preceded by treatment reductions. Patient/MD/DAS agreement of flare status is highest in patients worsening from R/LDA. OMERACT RA flare questions can discriminate between patients with/without flare and have strong evidence of construct and consequential validity. Ongoing work will identify optimal scoring and cut points to identify RA flares.