Corticosteroid treatment of multiple sclerosis relapses is associated with lower disability worsening over 5 years
Bibliographic record
Abstract
BACKGROUND: Corticosteroid treatment of multiple sclerosis (MS) relapses is assumed to improve the speed of relapse recovery, without modifying long-term disability risk. We aimed to re-evaluate this assumption in a large cohort of individuals with MS. METHODS: Individuals with clinically definite MS and ≥3 Expanded Disability Status Scale (EDSS) measurements over ≥12 months were identified within the international neuroimmunology registry MSBase. Individuals were required to have ≥1 relapse, with complete information on relapse treatment, phenotype and severity for all documented relapses. The primary outcome was disability worsening confirmed over 12 months. The association of the cumulative number of steroid-treated and untreated relapses (as a time-varying exposure) with disability worsening was evaluated with Cox proportional hazards. RESULTS: In total, 3673 individuals met the inclusion criteria (71% female, mean age 38 years, mean disability EDSS step 2); 5809 relapses (4671 treated/1138 untreated) were captured (annualised relapse rate 0.19). Over the study period (total 30 175 person-years), 32.7% reached the outcome of confirmed disability worsening (median survival time 5.2 years). Non-treated relapses were associated with a higher risk of disability worsening (HR 1.72, 95% CI 1.57 to 1.88) than steroid-treated relapses (HR 1.50, 95% CI 1.43 to 1.57). This association was modified by the efficacy of disease-modifying therapy at the time of relapse. CONCLUSIONS: Our results suggest that a lack of steroid treatment of MS relapses is associated with a higher risk of future disability worsening. Hence, corticosteroid treatment of MS relapses may impact not only the speed of recovery but also the severity of residual structural damage.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".