Open-label study of efgartigimod in seronegative myasthenia gravis
Bibliographic record
Abstract
Background: The ADAPT trial demonstrated the benefit of efgartigimod, a neonatal Fc receptor (FcRn) inhibitor, in acetylcholine receptor antibody (AChRAb) positive patients with generalized myasthenia gravis (MG). Information regarding the benefits in those lacking pathogenic antibodies is sparse. Objectives: We aimed to investigate the safety and efficacy of efgartigimod in patients with double-seronegative (SN) generalized MG. Design: An open-label 6-month prospective study, conducted at our center. Methods: Patients aged at least 18 years with clinical and electrodiagnostic features of MG and negative results for AChRAb and muscle-specific tyrosine kinase antibodies were included. Efgartigimod was administered weekly for 4 weeks and then biweekly for 5 months followed by an observation period. The primary endpoint was the change in MG impairment index (MGII) at 6 months compared to baseline. Secondary endpoints include the change in MG activities of daily living (MG-ADL), other MG scores, overall responders, and early responders. The safety analysis included all patients who received at least one dose of efgartigimod. Results: < 0.01) with efgartigimod treatment. The MG-ADL also improved. Seventy-two percent of patients were responders with 31% being early responders. Adverse events were reported in 83.3% of patients, and in 90.6%, they were mild. Headache was the most common, reported in 26.7%, followed by flu/common cold in 20%, and urinary tract infection in 13.3%. Conclusion: Efgartigimod was well tolerated and efficacious in patients with SN MG. Future randomized, placebo-controlled studies are needed. Trial registration: This trial is registered at ClinicalTrials.gov (NCT06587867), accessed via https://clinicaltrials.gov/study/NCT06587867?locStr=Toronto,%20ON,%20Canada&country=Canada&state=Ontario&city=Toronto&cond=Myasthenia%20Gravis&intr=efgartigimod&rank=1.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".