Effect of efgartigimod on muscle group subdomains in participants with generalized myasthenia gravis: post hoc analyses of the phase 3 pivotal <scp>ADAPT</scp> study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Generalized myasthenia gravis (gMG) is a rare, chronic, neuromuscular autoimmune disease mediated by pathogenic immunoglobulin G (IgG) autoantibodies. Patients with gMG experience debilitating muscle weakness, resulting in impaired mobility, speech, swallowing, vision and respiratory function. Efgartigimod is a human IgG1 antibody Fc fragment engineered for increased binding affinity to neonatal Fc receptor. The neonatal Fc receptor blockade by efgartigimod competitively inhibits endogenous IgG binding, leading to decreased IgG recycling and increased degradation resulting in lower IgG concentration. METHODS: The safety and efficacy of efgartigimod were evaluated in the ADAPT study. Key efficacy outcome measures included Myasthenia Gravis Activities of Daily Living (MG-ADL) and Quantitative Myasthenia Gravis (QMG) scores. Efgartigimod demonstrated significant improvement in both the MG-ADL and QMG scores. This post hoc analysis aimed to determine whether all subdomains of MG-ADL and QMG improved with efgartigimod treatment. Individual items of MG-ADL and QMG were grouped into four subdomains: bulbar, ocular, limb/gross motor and respiratory. Change from baseline over 10 weeks in each subdomain was calculated for each group. RESULTS: Greater improvements from baseline were seen across MG-ADL subdomains in participants treated with efgartigimod compared with placebo. These improvements were typically observed 1 to 2 weeks after the first infusion and correlated with reductions in IgG. Similar results were observed across most QMG subdomains. CONCLUSIONS: These post hoc analyses of MG-ADL and QMG subdomain data from ADAPT suggest that efgartigimod is beneficial in improving muscle function and strength across all muscle groups, leading to the observed efficacy in participants with gMG.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".