The effect of belimumab on mucocutaneous and vasculitis manifestations in patients with systemic lupus erythematosus: A large pooled post hoc analysis
Bibliographic record
Abstract
Objective To investigate the effects of belimumab (BEL) on systemic lupus erythematosus (SLE) mucocutaneous and vasculitis manifestations. Methods This post hoc, integrated Belimumab Summary of Lupus Efficacy (Be-SLE) analysis pooled data from five international Phase 3, randomized, placebo (PBO)-controlled BEL trials (BLISS-52 [NCT00424476; conducted in 2007–2009], BLISS-76 [NCT00410384; 2007–2009], BLISS-SC [NCT01484496; 2011–2015], North East Asia [NCT01345253; 2011–2015], EMBRACE [NCT01632241; 2013–2018]). Adults with active SLE and Safety of Estrogens in Lupus Erythematosus National Assessment-SLE Disease Activity Index (SELENA-SLEDAI) score ≥6 (BLISS-52, BLISS-76) or ≥8 (BLISS-SC, North East Asia, EMBRACE), randomized to BEL (10 mg/kg/month intravenously or 200 mg/week subcutaneously) or PBO, plus standard therapy (ST) were included. Mucocutaneous and vasculitis manifestations (listed below) were measured (baseline and every 4 weeks) for 52 weeks using SELENA-SLEDAI and British Isles Lupus Assessment Group (BILAG). Results Of 3086 patients (BEL, n = 1869; PBO, n = 1217), 85% (BEL and PBO) by SELENA-SLEDAI and 58% (BEL) and 62% (PBO) by BILAG (moderate or severe activity) had mucocutaneous manifestations, and <10% had vasculitis at baseline. At Week 52, significantly more BEL-treated than PBO-treated patients demonstrated improvements in SELENA-SLEDAI (59% vs 49%; p < .0001) and BILAG (54% vs 43%; p < .0001) mucocutaneous domains. Significant differences between-treatment favored BEL at Week 52 for resolution of all SELENA-SLEDAI items (vasculitis, rash, alopecia, and mucosal ulcers), and nine of 20 BILAG items (mild maculopapular eruption, localized active discoid lesions, mild alopecia, small mucosal ulceration, malar erythema, subcutaneous nodules, swollen fingers, major cutaneous vasculitis including ulcers, and minor cutaneous vasculitis). Conclusion Patients with SLE treated with BEL plus ST experienced significant improvements in most mucocutaneous and vasculitis manifestations compared with patients receiving PBO plus ST. These data provide additional support for the use of BEL in SLE and show that it is associated with skin improvements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.017 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".