Interferon beta-1b reduces black holes in a randomised trial of clinically isolated syndrome
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) is characterised by inflammatory lesions of the central nervous system. Interferon beta-1b (IFNB-1b) has been shown to improve clinical and magnetic resonance imaging (MRI) measures for patients with MS. OBJECTIVE: To evaluate whether IFNB-1b in patients presenting with clinically isolated syndromes (CIS) prevented persisting T1 hypointensities on MRI (persistent black holes (PBHs)). METHODS: In the placebo-controlled phase, patients (n = 468) were initially randomised to IFNB-1b (n = 292) or placebo (n = 176) for two years or clinically definite MS (CDMS). In the open-label phase (n = 418), both groups were offered IFNB-1b for up to five years. Lesions were classified as PBHs if T1 hypointensity persisted throughout the last available scan (minimum time one year). RESULTS: A total of 435 patients were evaluable for analysis. The number of PBHs/patient was lower in the early rather than the delayed treatment arm during both phases (.42 vs .71, p = .0102 and .70 vs 1.17, p = .0121). Exploratory analyses identified baseline characteristics that affected rate of conversion. CONCLUSIONS: Although the rate of lesions that converted to PBH showed no significant differences between groups, the numbers of PBHs per patient out of new lesions was significantly lower in IFNB-1b patients compared to patients on placebo. TRIAL REGISTRATION NUMBER: NCT00544037.
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How this classification was reachedexpand
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".