Phase <scp>2</scp> trial in acetylcholine receptor antibody‐positive myasthenia gravis of transition from intravenous to subcutaneous immunoglobulin: The <scp>MGSCIg</scp> study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Data on maintenance therapy with subcutaneous immunoglobulin (SCIg) in myasthenia gravis (MG) are limited. We report on transitioning acetylcholine receptor (AChR) antibody-positive (Ab+) MG patients on stable intravenous immunoglobulin (IVIg) regimens as part of routine clinical care to SCIg 1:1.2. METHODS: This multicenter North American open-label prospective investigator-initiated study had two components: the IVIg Stabilization Period (ISP) enrolling patients already on IVIg as part of routine clinical care (Weeks -10 to -1), followed by transition of stable MG subjects to SCIg in the Experimental Treatment Period (ETP; Weeks 0 to 12). We hypothesized that >65% of patients entering the ETP would have a stable Quantitative Myasthenia Gravis (QMG) score from Week 0 to Week 12. Secondary outcome measures included other efficacy measures, safety, tolerability, IgG levels, and treatment satisfaction. RESULTS: We recruited 23 patients in the ISP, and 22 entered the ETP. A total of 12 subjects (54.5%) were female, and 18 (81.8%) were White, with mean age 51.4 ± 17 years. We obtained Week 12 ETP QMG data on 19 of 22; one subject withdrew from ETP owing to clinical deterioration, and two subjects withdrew due to dislike of needles. On primary analysis, 19 of 22 participants (86.4%, 95% confidence interval = 0.72-1.00) were treatment successes using last observation carried forward (p = 0.018). Secondary efficacy measures supported MG stability. SCIg was safe and well tolerated, and IgG levels were stable. Treatment satisfaction was comparable between ISP and ETP. CONCLUSIONS: MG patients on IVIg as part of their routine clinical care remained stable on monthly IVIg dosage, and most maintained similar disease stability on SCIg.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".