Abstract
BackgroundPsoriatic arthritis (PsA) is characterized by a range of musculoskeletal and extra-articular disease manifestations. Composite indices are valuable tools to assess the multidimensional nature of PsA. The Psoriatic Arthritis Disease Activity Score (PASDAS)1 provides robust assessment of both joint and skin domains but is cumbersome to use in clinical practice. The Disease Activity Index for Psoriatic Arthritis (DAPSA)2 is relatively easy to use but does not assess skin disease.ObjectivesUsing pooled data from the phase 3 DISCOVER-1 and DISCOVER-2 studies of guselkumab (GUS) for the treatment of active PsA:3,4 (1) Describe the rate of achievement of a new composite endpoint combining DAPSA low disease activity (LDA; score ≤14, including remission) and Investigator Global Assessment (IGA) of psoriasis score ≤1 (range=0 [clear] to 4 [severe]); (2) Determine whether earlier (Week [W] 16) DAPSA LDA + IGA ≤1 is predictive of future achievement of minimal disease activity (MDA) or American College of Rheumatology (ACR) 50 response criteria; and (3) Contrast the performance of DAPSA LDA + IGA ≤1 with that of PASDAS LDA (score ≤3.2).MethodsPatients (pts) with active PsA despite standard therapies (DISCOVER-1: ≥3 swollen + ≥3 tender joints; CRP ≥0.3 mg/dL; ~30% had prior use of up to 2 TNF inhibitors; DISCOVER-2: ≥5 swollen + ≥5 tender joints; CRP ≥0.6 mg/dL; all pts were biologic-naïve) were randomized 1:1:1 to GUS 100 mg at W0, W4, then Q4W or Q8W; or placebo (PBO) with crossover to GUS Q4W at W24. In both studies, efficacy of GUS vs PBO was compared at W24 (primary endpoint). The number (%) of pts with DAPSA LDA + IGA ≤1 was determined at W24 for pts randomized to GUS or PBO. For all GUS-randomized pts, baseline variables associated with DAPSA LDA + IGA ≤1 and PASDAS LDA at W16 and the predictive value of W16 DAPSA LDA + IGA ≤1 or PASDAS LDA for achieving ACR50, MDA, and DAPSA LDA at W52 were assessed using logistic regression models.ResultsAt W24, DAPSA LDA + IGA ≤1 was met by 37% (277/748) of GUS-treated pts vs 13% (48/372) in the PBO group. At W16, 27% (203/748) of GUS-randomized pts had DAPSA LDA + IGA ≤1, and 22% (164/748) had PASDAS LDA. Among the 73% (545/748) of pts who did not have DAPSA LDA + IGA ≤1 at W16, most (77% [418/545]) had IGA ≤1 but not DAPSA LDA; 4% (23/545) had DAPSA LDA but not IGA ≤1, and 19% (104/545) had neither component. Baseline predictors of DAPSA LDA + IGA ≤1 at W16 were male gender, lower dactylitis score, lower Health Assessment Questionnaire-Disability Index (HAQ-DI) score, lower tender joint count (TJC), and higher Psoriasis Area and Severity Index (PASI) score. Baseline predictors of PASDAS LDA at W16 were younger age, lower dactylitis score, lower HAQ-DI score, lower TJC, and higher PASI score. As shown (Figure 1), pts who had DAPSA LDA + IGA ≤1 and PASDAS LDA at W16 were significantly more likely to achieve ACR50, MDA, and DAPSA LDA at W52 than pts without W16 responses; odds ratios (ORs) for achievement of ACR50, MDA, and DAPSA LDA responses at W52 were similar for pts who had DAPSA LDA + IGA ≤1 and for pts who had PASDAS LDA at W16. ORs for achievement of ACR50 and MDA at W52 were higher for pts who had both DAPSA LDA and IGA ≤1 at W16 (9.5 and 10.7) than for pts who had DAPSA LDA but not IGA ≤1 (6.5 and 3.5) or IGA ≤1 but not DAPSA LDA (1.6 and 1.5).ConclusionDAPSA LDA at W16 predicted future (W52) achievement of the stringent treatment targets of ACR50 and MDA; associations with W52 response were greater when W16 IGA ≤1 was added to DAPSA LDA. DAPSA LDA + IGA ≤1 at W16 as a predictor of W52 ACR50 and MDA response performed similarly to PASDAS LDA. The novel composite of DAPSA LDA + IGA ≤1 may be a reliable predictor of long-term PsA skin and joint response that is more practical to implement than the PASDAS.
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