3595 Effect of rozanolixizumab on ocular symptoms in generalised myasthenia gravis: <i>post hoc</i> item-level analysis of myasthenia gravis-specific outcomes in MycarinG
Bibliographic record
Abstract
Background Patients with generalised myasthenia gravis (gMG) may experience disabling ocular symptoms including diplopia/double vision and ptosis/eyelid drooping. In the Phase 3 MycarinG study ( NCT03971422), rozanolixizumab demonstrated clinically meaningful improvements across myasthenia gravis (MG)-specific outcomes and was generally well tolerated. Post hoc analyses investigated the effect of rozanolixizumab on ocular symptoms.Methods Adults with MGFA Disease Class II-IVa, acetylcholine receptor/muscle-specific tyrosine kinase autoantibody-positive gMG received once-weekly subcutaneous rozanolixizumab 7mg/kg, 10mg/kg or placebo for 6 weeks (to Day 43). Mean change from baseline (CFB) in ocular item scores across MG-Activities of Daily Living (MG-ADL), Quantitative MG (QMG) and MG Symptoms Patient-Reported Outcome (MG Symptoms PRO) Ocular Muscle Weakness scales for patients with baseline score ≥1 were assessed.Results 200 patients received rozanolixizumab 7mg/kg (n=66), 10mg/kg (n=67) or placebo (n=67). Mean baseline scores for ocular items were 1.6–1.9 for MG-ADL, 1.8–2.1 for QMG and 1.5–1.8 for MG Symptoms PRO. For rozanolixizumab 7mg/kg, 10mg/kg and placebo, mean CFB at Day 43 in MG-ADL ocular item scores was −0.6, −0.6 and −0.2, respectively, for diplopia, and −0.5, −0.7 and 0.0, respectively, for ptosis. Mean CFB in QMG scores was −0.6, −0.8 and 0.1, respectively, for diplopia, and −0.5, −1.0 and −0.5, respectively, for ptosis. Mean CFB in MG Symptoms PRO scores was −0.5, −0.6 and −0.2, respectively, for diplopia, and −0.5, −0.7 and −0.1, respectively, for ptosis. Most treatment-emergent adverse events were mild/moderate.Conclusions Rozanolixizumab demonstrated greater improvements in ocular item scores across MG-specific outcomes compared with placebo. 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".