The development of candidate composite disease activity and responder indices for psoriatic arthritis (GRACE project)

TLDR: Two new composite measures to assess disease activity in PsA have been developed by multiple linear regression and empirically, utilising physician-defined cut-offs for disease activity, and area under the receiver operating curves (AUC) were generally smaller.

Abstract: Objective To develop new composite disease activity indices for psoriatic arthritis (PsA). Methods Data from routine clinic visits at multiple centres were collected in a systematic manner. Data included all domains identified as important in randomised controlled trials in PsA. Decisions to change treatment were used as surrogates for high disease activity. New indices were developed by multiple linear regression (psoriatic arthritis disease activity score: PASDAS) and empirically, utilising physician-defined cut-offs for disease activity (arithmetic mean of desirability functions: AMDF). These were compared with existing composite measures: Composite Psoriatic arthritis Disease Activity Index (CPDAI), Disease Activity for PSoriatic Arthritis (DAPSA), and Disease Activity Score for rheumatoid arthritis (DAS28). Results 161/503 (32%) subjects had treatment changes. Although all measures performed well, compared with existing indices, PASDAS was better able to discriminate between high and low disease activity (area under receiver operating curves (ROC)) curve with 95% CI: PASDAS 0.773 (0.723, 0.822); AMDF 0.730 (0.680, 0.780); CPDAI 0.719 (0.668, 0.770); DAPSA 0.710 (0.654, 0.766); DAS28 0.736 (0.680, 0.792). All measures were able to discriminate between disease activity states in patients with oligoarthritis, although area under the receiver operating curves (AUC) were generally smaller. In patients with severe skin disease (psoriasis area and severity index >10) both nonparametric and AUC curve statistics were nonsignificant for all measures. Conclusions Two new composite measures to assess disease activity in PsA have been developed. Further testing in other datasets, including comparison with existing measures, is required to validate these instruments.