Moving toward earlier treatment of multiple sclerosis: Findings from a decade of clinical trials and implications for clinical practice
Bibliographic record
Abstract
The first clinical presentation of multiple sclerosis (MS) is usually a single episode of typical symptoms and signs and is designated a "first clinical demyelinating event" (FCDE) or a "clinically isolated syndrome". Patients with an FCDE who show 'silent' magnetic resonance imaging lesions are at high risk of further clinical events and therefore of meeting the criteria for the diagnosis of clinically definite MS (CDMS). Here we review five Phase III trials, in which treatment with the following disease-modifying drugs (DMDs) was initiated at this early stage: interferon beta (ETOMS, CHAMPS, BENEFIT, and REFLEX) and glatiramer acetate (PreCISe). Differences in the design of the trials and their patient inclusion criteria limit comparisons. However, the proportion of placebo-treated patients who developed CDMS within 2 years was 38-45% across studies, and this rate was significantly reduced by DMD treatment. Conversion to McDonald MS was reported by only two of the trials: BENEFIT (2001 criteria) and REFLEX (2005 criteria). Around 85% of placebo-treated patients developed McDonald MS by 2 years in each, and again a beneficial effect of DMD treatment was seen. Overall, these studies support early use of DMDs to treat patients with an FCDE who are at high risk of conversion to CDMS.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".