Glatiramer acetate in primary progressive multiple sclerosis: Results of a multinational, multicenter, double‐blind, placebo‐controlled trial
Bibliographic record
Abstract
OBJECTIVE: To determine whether glatiramer acetate (GA) slows accumulation of disability in primary progressive multiple sclerosis. METHODS: A total of 943 patients with primary progressive multiple sclerosis were randomized to GA or placebo (PBO) in this 3-year, double-blind trial. The primary end point was an intention-to-treat analysis of time to 1- (entry expanded disability status scale, 3.0-5.0) or 0.5-point expanded disability status scale change (entry expanded disability status scale, 5.5-6.5) sustained for 3 months. The trial was stopped after an interim analysis by an independent data safety monitoring board indicated no discernible treatment effect on the primary outcome. Intention-to-treat analyses of disability and magnetic resonance imaging end points were performed. RESULTS: There was a nonsignificant delay in time to sustained accumulated disability in GA- versus PBO-treated patients (hazard ratio, 0.87 [95% confidence interval, 0.71-1.07]; p = 0.1753), with significant decreases in enhancing lesions in year 1 and smaller increases in T2 lesion volumes in years 2 and 3 versus PBO. Post hoc analysis showed that survival curves for GA-treated male patients diverged early from PBO-treated male subjects (hazard ratio, 0.71 [95% confidence interval, 0.53-0.95]; p = 0.0193). INTERPRETATION: The trial failed to demonstrate a treatment effect of GA on primary progressive multiple sclerosis. Both the unanticipated low event rate and premature discontinuation of study medication decreased the power to detect a treatment effect. Post hoc analysis suggests GA may have slowed clinical progression in male patients who showed more rapid progression when untreated.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".