Patient subgroup analyses of the treatment effect of subcutaneous interferon β-1a on development of multiple sclerosis in the randomized controlled REFLEX study
Bibliographic record
Abstract
The REFLEX study (NCT00404352) established that subcutaneous (sc) interferon (IFN) β-1a reduced the risks of McDonald MS (2005 criteria) and clinically definite multiple sclerosis (CDMS) in patients with a first clinical demyelinating event suggestive of MS. The aim of this subgroup analysis was to assess the treatment effect of sc IFN β-1a in patient subgroups defined by baseline disease and demographic characteristics (age, sex, use of steroids at the first event, classification of first event as mono- or multifocal, presence/absence of gadolinium-enhancing lesions, count of <9 or ≥9 T2 lesions), and by diagnosis of MS using the revised McDonald 2010 MS criteria. Patients were randomized to the serum-free formulation of IFN β-1a, 44 μg sc three times weekly or once weekly, or placebo, for 24 months or until diagnosis of CDMS. Treatment effects of sc IFN β-1a on McDonald 2005 MS and CDMS in the predefined subgroups were similar to effects found in the intent-to-treat population. McDonald 2010 MS was retrospectively diagnosed in 37.7 % of patients at baseline. Both regimens of sc IFN β-1a significantly reduced the risk versus placebo of McDonald 2005 MS and CDMS, irrespective of McDonald 2010 status at baseline (risk reductions between 29 and 51 %). The effect of sc IFN β-1a was not substantially influenced by baseline patient demographic and disease characteristics, or baseline presence/absence of McDonald 2010 MS.
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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 | 0.021 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.016 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".