Rozanolixizumab in generalized myasthenia gravis: Pooled analysis of the Phase 3 MycarinG study and two open-label extensions
Bibliographic record
Abstract
BACKGROUND: Myasthenia gravis (MG) is a chronic autoimmune disease causing fluctuating muscle weakness. The MycarinG study showed that rozanolixizumab, a neonatal Fc receptor inhibitor, provided clinically meaningful improvements in MG outcomes in patients with acetylcholine receptor (AChR) and muscle-specific tyrosine kinase (MuSK) autoantibody-positive generalized MG (gMG). OBJECTIVE: We assessed efficacy and safety of 6-week rozanolixizumab treatment cycles in patients with gMG. METHODS: Following MycarinG, eligible patients enrolled in the open-label extension Phase 3 studies MG0004 (NCT04124965) to receive up to 52 weekly rozanolixizumab infusions or MG0007 (NCT04650854) to receive cycles of 6 weekly rozanolixizumab infusions (initiated on symptom worsening at investigators' discretion). To assess the effect of repeated cyclical treatment, data were pooled across MycarinG, MG0004 (first 6 weeks) and MG0007 (interim analysis). Efficacy endpoints included change from baseline in Myasthenia Gravis Activities of Daily Living (MG-ADL), Myasthenia Gravis Composite (MGC) and Quantitative Myasthenia Gravis (QMG) assessed in patients who received ≥2 symptom-driven treatment cycles. Treatment-emergent adverse events (TEAEs) were assessed in patients who received ≥1 cycle and had an (up to) 8-week follow-up period. RESULTS: At data cut-off (July 8, 2022), 188/196 (95.9%) patients received ≥1 treatment cycle with a follow-up period (primary safety pool; MycarinG/MG0007) and 127 (64.8%) received ≥2 symptom-driven cycles (primary efficacy pool; MycarinG/MG0004 [first 6 weeks]/MG0007). Consistent and clinically meaningful improvements in MG-ADL, MGC and QMG scores, and high MG-ADL, MGC and QMG response rates, were observed at the end of the first symptom-driven cycle and subsequent cycles. TEAEs were experienced by 169/188 (89.9%) patients and were mostly mild to moderate. TEAEs did not increase with repeated cycles. CONCLUSIONS: Repeated cycles of rozanolixizumab resulted in consistent, clinically meaningful improvements across cycles in MG-specific outcomes with an acceptable safety profile, supporting rozanolixizumab as a treatment option for adults with AChR and MuSK autoantibody-positive gMG.
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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 | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.015 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".