Randomized Trial of Oral Teriflunomide for Relapsing Multiple Sclerosis
Bibliographic record
Abstract
BACKGROUND: Teriflunomide is a new oral disease-modifying therapy for relapsing forms of multiple sclerosis. METHODS: We concluded a randomized trial involving 1088 patients with multiple sclerosis, 18 to 55 years of age, with a score of 0 to 5.5 on the Expanded Disability Status Scale and at least one relapse in the previous year or at least two relapses in the previous 2 years. Patients were randomly assigned (in a 1:1:1 ratio) to placebo, 7 mg of teriflunomide, or 14 mg of teriflunomide once daily for 108 weeks. The primary end point was the annualized relapse rate, and the key secondary end point was confirmed progression of disability for at least 12 weeks. RESULTS: Teriflunomide reduced the annualized relapse rate (0.54 for placebo vs. 0.37 for teriflunomide at either 7 or 14 mg), with relative risk reductions of 31.2% and 31.5%, respectively (P<0.001 for both comparisons with placebo). The proportion of patients with confirmed disability progression was 27.3% with placebo, 21.7% with teriflunomide at 7 mg (P=0.08), and 20.2% with teriflunomide at 14 mg (P=0.03). Both teriflunomide doses were superior to placebo on a range of end points measured by magnetic resonance imaging (MRI). Diarrhea, nausea, and hair thinning were more common with teriflunomide than with placebo. The incidence of elevated alanine aminotransferase levels (≥1 times the upper limit of the normal range) was higher with teriflunomide at 7 mg and 14 mg (54.0% and 57.3%, respectively) than with placebo (35.9%); the incidence of levels that were at least 3 times the upper limit of the normal range was similar in the lower- and higher-dose teriflunomide groups and the placebo group (6.3%, 6.7%, and 6.7%, respectively). Serious infections were reported in 1.6%, 2.5%, and 2.2% of patients in the three groups, respectively. No deaths occurred. CONCLUSIONS: Teriflunomide significantly reduced relapse rates, disability progression (at the higher dose), and MRI evidence of disease activity, as compared with placebo. (Funded by Sanofi-Aventis; TEMSO ClinicalTrials.gov number, NCT00134563.).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".