Magnetic resonance active lesions as individual-level surrogate for relapses in multiple sclerosis
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: Use of quantitative magnetic resonance imaging (MRI) metrics as surrogates for clinical outcomes in multiple sclerosis (MS) trials is controversial. OBJECTIVES: We sought to validate, at the individual-patient level, the number of MRI active lesions, as a surrogate marker for relapses in MS. METHODS: Individual-patient data from two large, placebo-controlled clinical trials of subcutaneous interferon β-1a in patients with relapsing-remitting or secondary progressive (SP) MS were analysed separately and as pooled data. The four Prentice criteria were applied to assess surrogacy for the number of new T2 MRI lesions. The predictive value of short-term treatment effects on this MRI marker for longer-term clinical relapses was also assessed. RESULTS: All Prentice criteria were satisfied. The number of new T2 MRI lesions correlated with the number of relapses over the follow-up period. The proportion of treatment effect on relapses accounted for by the effect of treatment on new T2 MRI lesions over 2 years was 53% in patients with relapsing-remitting MS, 67% in patients with secondary progressive MS, and 62% in pooled data. In the pooled data, treatment effects on new lesions over 1 year mediated a good proportion (70%) of effects on relapses over the subsequent year. CONCLUSIONS: This study provides evidence that new T2 MRI lesion count is a surrogate for relapses in patients with MS treated with interferon or drugs with a similar mechanism of action. Short-term treatment effects on this MRI measure can predict longer-term effects on relapses.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.000 | 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