P.099 Post-hoc evaluation of the clinical effects of nipocalimab, a neonatal fragment crystallizable blocker, over time in the Vivacity MG3 study
Bibliographic record
Abstract
Background: In generalized myasthenia gravis (gMG), there remains an unmet need for treatments providing meaningful symptom control. Methods: Mean changes in MG-ADL were compared between nipocalimab + standard-of-care (SoC) and placebo+SoC. The proportion of patients achieving: Minimal Symptom Expression (MSE), MG-ADL score 0/1, time with MSE, sustained within person meaningful change (WPMC) starting from Week 4, and time spent with WPMC were compared. Results: Nipocalimab+SoC demonstrated significant improvement in MG-ADL compared to placebo+SOC, LS-mean-change[SE] -4.7[0.329] vs -3.25[0.335]; Difference in means[SE]=-1.45 [0.470], p=0.002. The mean difference favoured nipocalimab+SoC, and was significant as early as week 1: LS-mean-change[SE]: -2.72[2.979] vs -1.77[2.426]; Difference in means[SE] -0.82[0.410], p=0.046. Nipocalimab+SoC patients were three times more likely to achieve MSE at any point during the study vs placebo; Odds Ratio[95% CI]: 3.0[1.3, 6.8]; 31.2% vs. 13.2%. For the 25 patients reaching MSE, the time sustaining MSE [percent time with MSE] was 101.5 days, (60.4%, nipocalimab+SOC) vs 55 days, (32.7%, placebo+SOC). Similarly, the proportion of patients with sustained WPMC favored nipocalimab+SOC, 55.8% vs 26.3%, placebo+SOC, p<0.001. The median percent time spent with WPMC was 84.5%, nipocalimab+SOC vs 39.9%, placebo+SOC, p=0.007. Conclusions: Based on MG-ADL data from Phase 3, nipocalimab an FcRn blocker, demonstrated rapid, substantial, and sustained symptom control.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".