Efficacy of subcutaneous interferon -1a on MRI outcomes in a randomised controlled trial of patients with clinically isolated syndromes
Bibliographic record
Abstract
AIM: The REbif FLEXible dosing in early MS (REFLEX) study compared several brain MRI outcomes in patients presenting with clinically isolated syndromes suggestive of multiple sclerosis and treated with two dose-frequencies of subcutaneous interferon (IFN) β-1a or placebo. METHODS: Patients were randomised (1:1:1) to IFN β-1a, 44 µg subcutaneously three times a week or once a week, or placebo three times a week for up to 24 months. MRI scans were performed every 3 months, or every 6 months if the patient developed clinically definite multiple sclerosis. End points analysed included: number of combined unique active lesions per patient per scan; numbers and volumes of new T2, T1 hypointense and gadolinium-enhancing (Gd+) lesions per patient per scan; and brain volume. RESULTS: 517 patients were randomised (intent-to-treat population: subcutaneous IFN β-1a three times a week, n=171; subcutaneous IFN β-1a once a week, n=175; placebo, n=171). Combined unique active lesions were lower in patients treated with subcutaneous IFN β-1a versus placebo (mean (SD) lesions per patient per scan: three times a week 0.6 (1.15); once a week 1.23 (4.26); placebo 2.70 (5.23); reduction versus placebo: three times a week 81%; once a week 63%; p<0.001) and with three times a week versus once a week (48% reduction; p=0.002). The mean numbers of new T2, T1 hypointense and Gd+ lesions were all significantly lower in the two active treatment arms compared with placebo (p≤0.004 for three times a week or once a week) and in the three times a week group compared with once a week (p≤0.012). CONCLUSIONS: Both subcutaneous IFN β-1a 44 µg regimens improved MRI outcomes versus placebo, with the three times a week regimen having a more pronounced effect than once a week dosing. TRIAL REGISTRATION: clinicaltrial.gov identifier, NCT00404352.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".