Risk of secondary progressive multiple sclerosis after early worsening of disability
Bibliographic record
Abstract
BACKGROUND: Whether progression independent of relapse activity (PIRA) heralds earlier onset of secondary progressive multiple sclerosis (SPMS) and more rapid accumulation of disability during SPMS remains to be determined. We investigated the association between early PIRA, relapse-associated worsening (RAW) of disability and time to SPMS, subsequent disability progression and their response to therapy. METHODS: This observational cohort study included patients with relapsing-remitting multiple sclerosis (RRMS) from the MSBase international registry across 146 centres and 39 countries. Associations between the number of PIRA and RAW during early multiple sclerosis (MS) (the initial 5 years of MS onset) were analysed with respect to: time to SPMS using Cox proportional hazards models adjusted for disease characteristics; and disability progression during SPMS, calculated as the change of Multiple Sclerosis Severity Scores over time, using multivariable linear regression. RESULTS: 10 692 patients met the inclusion criteria: 3125 (29%) were men and the mean MS onset age was 32.2 years. A higher number of early PIRA (HR=1.50, 95% CI 1.28 to 1.76, p<0.001) and RAW (HR=2.53, 95% CI 2.25 to 2.85, p<0.001) signalled a higher risk of SPMS. A higher proportion of early disease-modifying therapy exposure (per 10%) reduced the effect of early RAW (HR=0.94, 95% CI 0.89 to 1.00, p=0.041) but not PIRA (HR=0.97, 95% CI 0.91 to 1.05, p=0.49) on SPMS risk. No association between early PIRA/RAW and disability progression during SPMS was found. CONCLUSIONS: Early disability increase during RRMS is associated with a greater risk of SPMS but not the rate of disability progression during SPMS. The deterioration associated with early relapses represents a potentially treatable risk factor of SPMS. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry (ACTRN12605000455662).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".