3390 Effect of zilucoplan on myasthenia gravis-specific outcome subdomain scores in RAISE: a phase 3 study
Bibliographic record
Abstract
Background In RAISE ( NCT04115293; Phase 3 study), zilucoplan, a macrocyclic peptide complement component 5 inhibitor, demonstrated rapid and clinically meaningful improvements in Myasthenia Gravis Activities of Daily Living (MG-ADL) and Quantitative Myasthenia Gravis (QMG) total scores versus placebo in adults with acetylcholine receptor autoantibody-positive generalised myasthenia gravis. We evaluated the effect of zilucoplan on MG-ADL and QMG subdomain scores (ocular, bulbar, respiratory and limb/axial).Methods Patients were randomised to zilucoplan 0.3mg/kg (n=86) or placebo (n=88) for 12 weeks. Primary endpoint: change from baseline (CFB) in MG-ADL total score at Week 12. Exploratory analyses assessed CFB in MG-ADL and QMG subdomain scores for patients with baseline score ≥1.Results At Week 12, least-squares mean (LSM) (95% CI) CFB in MG-ADL total score was: zilucoplan –4.39 (–5.28, –3.50) and placebo –2.30 (–3.17, –1.43); difference –2.09 [–3.24, –0.95]; p=0.0004. LSM CFB in QMG total score was: zilucoplan –6.19 (–7.29, –5.08) and placebo –3.25 (–4.32, –2.17); difference –2.94 (–4.39, –1.49); p<0.0001. Mean (standard deviation [SD]) CFB in MG-ADL subdomain scores (zilucoplan vs placebo) were: ocular, –1.5 (1.7) vs –0.8 (1.6); bulbar, –1.9 (1.8) vs –1.1 (1.7); respiratory, –0.4 (0.6) vs –0.3 (0.7); limb/axial, −1.2 (1.5) vs –0.8 (1.4), respectively. Mean (SD) CFB in QMG subdomain scores were: ocular, −2.0 (2.1) vs −1.3 (2.2); bulbar, −1.6 (1.4) vs −1.1 (1.5); respiratory, −0.6 (0.7) vs −0.3 (0.8); limb/axial, −2.9 (2.6) vs −1.2 (2.4), respectively.Conclusion Zilucoplan demonstrated improvements versus placebo across all subdomain scores in MG-ADL and QMG. Funding: UCB.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".