P.096 Final pooled analysis of efficacy and safety of rozanolixizumab cycles in patients with generalised myasthenia gravis: MycarinG and open-label extension studies
Bibliographic record
Abstract
Background: In the Phase 3 MycarinG study (MG0003/NCT03971422), one 6-week cycle of rozanolixizumab significantly improved myasthenia gravis (MG)-specific outcomes versus placebo. After MycarinG, patients could enrol in open-label extension studies (MG0004 then MG0007, or MG0007 directly). Methods: In MG0004 (NCT04124965), patients received once-weekly rozanolixizumab 7mg/kg or 10mg/kg for ≤52 weeks. In MG0007 (NCT04650854), after a cycle of rozanolixizumab 7mg/kg or 10mg/kg, subsequent cycles were based on symptom worsening at the investigator’s discretion. Pooled data are reported across MycarinG, MG0004 (first 6 weeks) and MG0007 (final data) for patients receiving ≥2 symptom-driven cycles (efficacy; ≤13 cycles) or ≥1 cycle (safety). Results: 196 patients received ≥1 rozanolixizumab dose of whom 129 received ≥2 symptom-driven cycles (7mg/kg: n=70; 10mg/kg: n=59). Treatment response was maintained from Cycles 1–13: mean change from baseline to Day 43 in MG-Activities of Daily Living score ranged from -3.2 to -4.9 (7mg/kg) and -3.2 to -6.7 (10mg/kg). Quantitative MG and MG Composite scores also improved. Treatment-emergent adverse events (TEAEs) did not increase with repeated cyclic treatment, and most were mild/moderate; the most common event was headache. Conclusions: Rozanolixizumab showed consistent improvements across MG-specific outcomes up to 13 cycles and repeated cyclic treatment was generally well tolerated. 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 | 0.028 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.025 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".