European/Canadian multicenter, double‐blind, randomized, placebo‐controlled study of the effects of glatiramer acetate on magnetic resonance imaging–measured disease activity and burden in patients with relapsing multiple sclerosis
Bibliographic record
Abstract
Abstract Two prior double‐blind, placebo‐controlled, randomized trials demonstrated that glatiramer acetate (GA) reduces relapse rates in patients with relapsing remitting multiple sclerosis (RRMS). This study was designed to determine the effect, onset, and durability of any effect of GA on disease activity monitored with magnetic resonance imaging (MRI) in patients with RRMS. Two hundred thirty‐nine eligible patients were randomized to receive either 20 mg GA ( n = 119) or placebo ( n = 120) by daily subcutaneous injection. Eligibility required one or more relapses in the 2 years before entry and at least one enhancing lesion on a screening MRI. The study was a randomized, double‐blind, placebo‐controlled phase during which all patients studied underwent monthly MRI scans and clinical assessments over 9 months. The primary outcome measure was the total number of enhancing lesions on T1‐weighted images. Secondary outcome measures included the proportion of patients with enhancing lesions, the number of new enhancing lesions and change in their volume; the number of new lesions detected on T2‐weighted images and change in their volume, and the change in volume of hypointense lesions seen on unenhanced T1‐weighted images. Clinical measures of disease activity were also evaluated. The active treatment and placebo groups were comparable at entry for all demographic, clinical, and MRI variables. Treatment with GA showed a significant reduction in the total number of enhancing lesions compared with placebo (−10.8, 95% confidence interval −18.0 to −3.7; p = 0.003). Consistent differences favoring treatment with GA were seen for almost all secondary end points examined: number of new enhancing lesions ( p < 0.003), monthly change in the volume of enhancing lesions ( p = 0.01), and change in volume ( p = 0.006) and number of new lesions seen on T2‐weighted images ( p < 0.003). The relapse rate was also significantly reduced by 33% for GA‐treated patients ( p = 0.012). All effects increased over time. Glatiramer acetate significantly reduced MRI‐measured disease activity and burden. Ann Neurol 2001;49:290–297
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".