AI Article Synopsis

  • The study aimed to understand how systemic lupus erythematosus (SLE) progresses after starting therapy, focusing on different patient responses and outcomes.
  • Researchers analyzed data from 2868 patients across four clinical trials, identifying four distinct disease evolution characteristics based on both clinical measures and patient-reported outcomes.
  • The findings suggest that categorizing patients into these trajectories could help personalize treatments and improve future clinical study designs, as no single factor can predict how SLE will progress.

Article Abstract

Objective: Upon commencement of therapy for active disease, patients with systemic lupus erythematosus (SLE) show varying evolution regarding disease activity measures and patient-reported outcomes (PROs). Our objective was to identify disease evolution trajectories to gain a deeper understanding of SLE progression, ultimately improving future trial design.

Methods: Patients with ≥2 visits and available data on SLEDAI-2K, BILAG, PGA, FACIT-F, and glucocorticoid use were included in a post-hoc analysis of four randomised controlled trials of belimumab (BLISS-52, BLISS-76, BLISS-SC, EMBRACE). Growth mixture modelling identified latent classes.

Results: Among 2868 patients analysed, baseline median disease duration was 4.5 (IQR: 1.5-9.7) years and mean (± standard deviation) SDI 0.7 (±2.0), SLEDAI-2K 10.2 (±3.6), BILAG 17.0 (±7.8), PGA 1.5 (±0.5), FACIT-F 30.6 (±11.9), and prednisone dose 11.0 (±8.9) mg/day. In the initial model, glucocorticoid use and dose yielded high standard errors, indicating a weak link with the latent process. A refined model considered only clinical measures and FACIT-F, corrected for intervention and SDI; no other covariates improved the fit. Four classes best described disease evolution: highly active, responders; highly active, non-responders; moderately active, responders; moderately active, non-responders. LLDAS and DORIS remission attainment associated with latent classes.

Conclusion: By linking disease activity measures with PROs, we identified four distinct trajectories describing SLE evolution following the initiation of therapy. This classification could be valuable for personalising treatment and guiding biological studies aimed at distinguishing patients with varying anticipated treatment responses, as no single clinical variable alone can predict disease progression.

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http://dx.doi.org/10.1093/rheumatology/keae575DOI Listing

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