Filling the "GAP" in Real-World Assessment of Psoriatic Arthritis Disease Activity: Performance Characteristics of a Global/Pain Composite Endpoint

Introduction: Some retrospective data sources, such as electronic health records in the USA, report composite outcome measures not fully validated in psoriatic arthritis (PsA). However, they often contain global assessments, such as a Physician Global Assessment (PhGA) and Patient Global Assessment (PatGA), along with patient-reported pain scores, which individually are considered validated in PsA. This research described the performance characteristics of a 3-item global assessment and pain (GAP) composite endpoint using data from the ixekizumab phase 3 PsA clinical trial program. 

Methods: Discrimination of GAP was assessed by comparing placebo to active treatment arms. The magnitude of treatment effect and responsiveness were compared to Disease Activity Index for PsA (DAPSA), clinical DAPSA, DAPSA28, and Psoriatic Arthritis Disease Activity Score (PASDAS) using effect size (ES) and standardized response mean (SRM), respectively. Construct validity was evaluated through correlation among the composite endpoints, and with other physician- and patient-reported outcomes. Change in GAP was compared in patients who reached low disease activity (LDA) levels based on DAPSA, cDAPSA, and PASDAS vs those who did not. 

Results: GAP discriminated between active treatment and placebo with statistically significant separation as early as week 1. The largest ES/SRM was seen with GAP (2.29/1.74) and PASDAS (2.47/1.68). GAP had the strongest correlation with PASDAS (0.81–0.92) and showed moderate correlations with patient-assessed physical function, low correlations with physician-assessed skin and nail psoriasis, and low to moderate correlation with physician-assessed enthesitis. A significantly greater improvement in GAP was seen in the groups achieving LDA states compared to those not (p < 0.001). 

Conclusion: The GAP composite, an abbreviated endpoint comprising measures common in electronic health records, has promising performance characteristics and could be used to address important clinical questions regarding outcomes and impact of PsA in existing datasets. ClinTrials.gov Identifier: NCT01695239; NCT02349295.