Teriflunomide versus subcutaneous interferon beta-1a in patients with relapsing multiple sclerosis: a randomised, controlled phase 3 trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In previous studies, teriflunomide significantly reduced the annualised relapse rate (ARR) and disability progression. OBJECTIVE: This phase 3, rater-blinded study (NCT00883337) compared teriflunomide with interferon-beta-1a (IFNβ-1a). METHODS: Patients with relapsing multiple sclerosis were randomised (1:1:1) to oral teriflunomide 7-or 14 mg, or subcutaneous IFNβ-1a 44 µg. The primary composite endpoint was time to failure, defined as first occurrence of confirmed relapse or permanent treatment discontinuation for any cause. Secondary endpoints included ARR, Fatigue Impact Scale (FIS) and Treatment Satisfaction Questionnaire for Medication (TSQM). The study was completed 48 weeks after the last patient was randomised. RESULTS: Some 324 patients were randomised (IFNβ-1a: 104; teriflunomide 7 mg: 109; teriflunomide 14 mg: 111). No difference in time to failure was observed. There was no difference in ARR between teriflunomide 14 mg and IFNβ-1a, but ARR was significantly higher with teriflunomide 7 mg. FIS scores indicated more frequent fatigue with IFNβ-1a, though differences were only significant with teriflunomide 7 mg. TSQM scores were significantly higher with teriflunomide. There were no unexpected safety findings. CONCLUSION: Effects on time to failure were comparable between teriflunomide and IFNβ-1a. There was no difference between teriflunomide 14 mg and IFNβ-1a on ARR, though ARR was higher with teriflunomide 7 mg. The teriflunomide safety profile was consistent with previous studies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it