Improvement in relapse recovery with peginterferon beta-1a in patients with multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Subcutaneous peginterferon beta-1a every 2 weeks significantly affects clinical outcomes in patients with relapsing-remitting multiple sclerosis (RRMS). OBJECTIVES: To explore relationships between relapses and worsening of disability in patients with RRMS, and assess the treatment effect of peginterferon beta-1a on relapse recovery. METHODS: Post-hoc analysis of the 2-year, randomized, double-blind, parallel-group, Phase 3 ADVANCE study. The severity of relapses, proportion of patients with relapses associated with residual disability (onset of 24-week confirmed disability progression (CDP) within 90 days following a relapse), and persistence of changes in Functional Systems Scores, were compared between treatment groups. RESULTS: = 0.02). Reduction in relapses associated with residual disability was greater than the treatment effect on overall relapse rate, and occurred despite similar relapse severity across treatment groups. CONCLUSIONS: The beneficial effect of peginterferon beta-1a on risk of CDP may be attributable to the combination of an overall reduction in the risk of relapses and improvement in recovery from relapses, thus limiting further disability progression. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00906399.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".