Relapse recovery in relapsing–remitting multiple sclerosis: An analysis of the CombiRx dataset
Bibliographic record
Abstract
BACKGROUND: Clinical relapses are the defining feature of relapsing forms of multiple sclerosis (MS), but relatively little is known about the time course of relapse recovery. OBJECTIVE: The aim of this study was to investigate the time course of and patient factors associated with the speed and success of relapse recovery in people with relapsing-remitting MS (RRMS). METHODS: Using data from CombiRx, a large RRMS trial (clinicaltrials.gov identifier NCT00211887), we measured the time to recovery from the first on-trial relapse. We used Kaplan-Meier survival analyses and Cox regression models to investigate the association of patient factors with the time to unconfirmed and confirmed relapse recovery. RESULTS: CombiRx included 1008 participants. We investigated 240 relapses. Median time to relapse recovery was 111 days. Most recovery events took place within 1 year of relapse onset: 202 of 240 (84%) individuals recovered during follow-up, 161 of 202 (80%) by 180 days, and 189 of 202 (94%) by 365 days. Relapse severity was the only factor associated with relapse recovery. CONCLUSION: Recovery from relapses takes place up to approximately 1 year after the event. Relapse severity, but no other patient factors, was associated with the speed of relapse recovery. Our findings inform clinical practice and trial design in RRMS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".