OP0025 FACTORS ASSOCIATED WITH FATIGUE AND ITS IMPROVEMENT – A PRINCIPAL COMPONENT ANALYSIS OF PATIENTS WITH ACTIVE PSORIATIC ARTHRITIS FROM GUSELKUMAB PHASE 3 TRIALS

Abstract

BackgroundFatigue, one of the top 3 patient (pt)-reported symptoms of psoriatic arthritis (PsA) and a recent PsA outcome domain,1 causes impaired health-related quality-of-life, diminished productivity, and disability.1-3 Although the origins of fatigue are multifactorial, inflammation is hypothesized to play an important role.4 In pts with active PsA, treatment with guselkumab (GUS) led to clinically meaningful and sustained improvements in fatigue through 1 year in DISCOVER-1 (D1) and DISCOVER-2 (D2).5ObjectivesTo identify 1) factors associated with fatigue and 2) factors associated with change in fatigue among pts with PsA treated with GUS.MethodsIn the Phase 3 D1 (N=381, biologic-naïve and tumor necrosis factor inhibitor-experienced) and D2 (N=739, biologic-naïve) studies, pts with active PsA despite standard therapies and/or biologic disease-modifying antirheumatic drugs were randomized 1:1:1 to GUS 100 mg every 4 weeks (Q4W); GUS 100 mg at W0, W4, then Q8W; or placebo (PBO) with crossover to GUS 100 mg Q4W at W24. The pt-reported Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-Fatigue) scale measured fatigue (scored 0-52). In these post-hoc analyses of D1 and D2 pts, a principal component analysis (PCA) was performed using W0 data to identify the underlying baseline factors associated with fatigue. Additionally, linear regression analyses were performed to identify covariates associated with change in fatigue from W0 to W24.ResultsIn 1120 pts (mean age 47 yrs, mean disease duration 5.9 yrs, 48% female), mean FACIT-Fatigue scores at baseline ranged from 29.1 to 31.4 (vs 43.6 for the general US population).5 PCA showed that 62% of the variability in fatigue could be explained by 3 components (Figure 1). The first component, explaining 34% of variability in fatigue, largely comprised systemic disease activity and function measures such as pain, pt global assessment of disease activity (PtGDA), physician’s global assessment of disease activity, and Health Assessment Questionnaire-Disability Index (HAQ-DI). The second component, explaining 16% of variability, comprised joint manifestations including swollen joint count (SJC) and tender joint count (TJC). Skin involvement as assessed by Psoriasis Area and Severity Index (PASI) and systemic inflammation (C-reactive protein [CRP]) could explain 12% of the variability in fatigue (Figure 1 and Table 1). In a multivariate linear regression analysis, after adjusting for effects from other variables, improvement in CRP, physical function (HAQ-DI), PtGDA, and PASI score were significantly associated with fatigue improvement in GUS-treated pts at W24 (all p<0.001).Table 1.PCA of Pts With Active PsA in D1+D2 (N=1120; Pooled W0 data): Factor Loading Estimates by CovariatesComponent1 Systemic Disease Activity and FunctionComponent 2 Joint ManifestationsComponent 3 Skin Involvement and InflammationPsA disease duration, yr0.100.140.25PASI total score (0-72)0.220.230.74CRP, mg/dL0.36-0.130.55HAQ-DI score (0-3)0.73-0.09-0.19Pain (0-10 VAS)0.83-0.35-0.13PtGDA (0-10 VAS)0.82-0.36-0.16Physician global assessment of disease activity (0-10 VAS)0.65-0.180.23SJC (0-66)0.500.74-0.12TJC (0-68)0.540.70-0.18VAS=Visual Analog Scale.ConclusionAmong pts with PsA, measures of systemic disease activity and function, followed by joint manifestations, and skin involvement/inflammation accounted for 62% of the variability in fatigue. The large residual effect (38%) that was unexplained by the current model suggests the need for further research to identify additional factors (eg, distinct molecular pathways) contributing to the fatigue reported by PsA pts.