Comparative effectiveness of glatiramer acetate and interferon beta formulations in relapsing–remitting multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: The results of head-to-head comparisons of injectable immunomodulators (interferon β, glatiramer acetate) have been inconclusive and a comprehensive analysis of their effectiveness is needed. OBJECTIVE: We aimed to compare, in a real-world setting, relapse and disability outcomes among patients with multiple sclerosis (MS) treated with injectable immunomodulators. METHODS: Pairwise analysis of the international MSBase registry data was conducted using propensity-score matching. The four injectable immunomodulators were compared in six head-to-head analyses of relapse and disability outcomes using paired mixed models or frailty proportional hazards models adjusted for magnetic resonance imaging variables. Sensitivity and power analyses were conducted. RESULTS: Of the 3326 included patients, 345-1199 patients per therapy were matched (median pairwise-censored follow-up was 3.7 years). Propensity matching eliminated >95% of the identified indication bias. Slightly lower relapse incidence was found among patients treated with glatiramer acetate or subcutaneous interferon β-1a relative to intramuscular interferon β-1a and interferon β-1b (p≤0.001). No differences in 12-month confirmed progression of disability were observed. CONCLUSION: Small but statistically significant differences in relapse outcomes exist among the injectable immunomodulators. MSBase is sufficiently powered to identify these differences and reflects practice in tertiary MS centres. While the present study controlled indication, selection and attrition bias, centre-dependent variance in data quality was likely.
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".