Randomized study of adjunctive belimumab in participants with generalized myasthenia gravis
Bibliographic record
Abstract
OBJECTIVE: To investigate the efficacy and safety of belimumab, a fully human immunoglobulin G1λ monoclonal antibody against B-lymphocyte stimulator, in participants with generalized myasthenia gravis (MG) who remained symptomatic despite standard of care (SoC) therapy. METHODS: Eligible participants with MG were randomized 1:1 to receive IV belimumab 10 mg/kg or placebo in this phase II, placebo-controlled, multicenter, double-blind study (NCT01480596; BEL115123). Participants received SoC therapies throughout the 24-week treatment phase and 12-week follow-up period. The primary efficacy endpoint was mean change from baseline in the Quantitative Myasthenia Gravis (QMG) scale at week 24; safety assessments included the frequency and severity of adverse events (AEs) and serious AEs. RESULTS: = 0.256). There were no statistically significant differences between treatment groups for secondary endpoints, including the MG Composite and MG-Activity of Daily Living scores. Acetylcholine receptor antibody levels decreased over time in both treatment groups. No unexpected AEs were identified and occurrence was similar in the belimumab (78%) and placebo (91%) groups. One participant receiving placebo died (severe sepsis) during the treatment phase. CONCLUSIONS: The primary endpoint was not met for belimumab in participants with generalized MG receiving SoC. There was no significant difference in mean change in the QMG score at week 24 for belimumab vs placebo. The safety profile of belimumab was consistent with previous systemic lupus erythematosus studies. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that for participants with generalized MG, belimumab did not significantly improve QMG score compared with placebo.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".