Responsiveness of patient-reported outcomes by disease trajectory in systemic lupus erythematosus

Abstract Objectives Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with persistent symptoms that profoundly impair quality of life yet are often under-recognized by clinician-assessed instruments. Patient-reported outcomes (PROs) are increasingly incorporated in clinical trials to capture treatment benefit from the patient perspective. However, the responsiveness of PRO instruments and their alignment with clinician-assessed disease activity across distinct SLE trajectories remain incompletely defined. We evaluated the longitudinal responsiveness and convergent validity of PRO measures across predefined disease trajectory classes. Methods Secondary analysis of pooled patient-level data from two phase III randomized clinical trials of belimumab in adults with active SLE (n = 1908), stratified into four previously derived trajectory classes defined by baseline disease activity and treatment response. PROs included FACIT-Fatigue, SF-36 PCS and MCS, EQ-5D-3L, and EQ-VAS. Responsiveness was quantified using standardized response means (SRMs). Convergent validity was evaluated using repeated-measures correlations between within-person changes in PROs and clinician-assessed disease activity measures (SLEDAI-2K, BILAG, and PGA), with sensitivity analyses performed to assess the robustness of findings. Results FACIT-F and SF-36 PCS generally demonstrated the greatest responsiveness, while EQ-5D-3L showed smaller changes and less consistent responsiveness across classes and timepoints. FACIT-F demonstrated early responsiveness, whereas SF-36 PCS showed sustained responsiveness over later follow-up. PRO changes were most consistently associated with PGA. Sensitivity analyses showed broadly similar patterns. Conclusion FACIT-F and SF-36 PCS demonstrated the greatest responsiveness and alignment with clinician-assessed disease activity. EQ-5D-3L showed less consistent responsiveness, suggesting domain-specific PROs may better capture treatment benefit in SLE trials and health technology assessments.