Efficacy of delayed‐release dimethyl fumarate in relapsing‐remitting multiple sclerosis: integrated analysis of the phase 3 trials
Bibliographic record
Abstract
OBJECTIVE: Obtain a more precise estimate of the efficacy of delayed-release dimethyl fumarate (DMF; also known as gastro-resistant DMF) in relapsing multiple sclerosis (MS) and examine the consistency of DMF's effects across patient subgroups stratified by baseline demographic and disease characteristics. METHODS: A prespecified integrated analysis of the randomized, double-blind, placebo-controlled, Phase 3 DEFINE and CONFIRM trials was conducted. RESULTS: The intent-to-treat population comprised 2301 patients randomized to receive placebo (n = 771) or DMF 240 mg twice daily (BID; n = 769) or three times daily (TID; n = 761). At 2 years, DMF BID and TID reduced the annualized relapse rate by 49% and 49% (both P < 0.0001), risk of relapse by 43% and 47% (both P < 0.0001), risk of 12-week confirmed disability progression by 32% (P = 0.0034) and 30% (P = 0.0059), and risk of 24-week confirmed disability progression by 29% (P = 0.0278) and 32% (P = 0.0177), respectively, compared with placebo. In a subset of patients (MRI cohort), DMF BID and TID reduced the mean number of new/enlarging T2-hyperintense lesions by 78% and 73%, gadolinium-enhancing lesion activity by 83% and 70%, and mean number of new nonenhancing T1-hypointense lesions by 65% and 64% (all P < 0.0001 vs. placebo). Effects were generally consistent across patient subgroups. INTERPRETATION: The integrated analysis provides a more precise estimate of DMF's efficacy. DMF demonstrated a robust reduction in disease activity and a consistent therapeutic effect across patient subgroups.
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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 | 0.026 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".