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

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.