Sustained improvement in Expanded Disability Status Scale as a new efficacy measure of neurological change in multiple sclerosis: treatment effects with natalizumab in patients with relapsing multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Validated measures of sustained improvements in neurological function have not been established for multiple sclerosis (MS) clinical studies. OBJECTIVE: To evaluate sustained Expanded Disability Status Scale (EDSS) change as a potential indicator of neurological improvement and as an outcome measure in MS clinical studies. METHODS: Analyses were performed on patients (n = 620) from the pivotal natalizumab study AFFIRM with baseline EDSS scores ≥2.0. Cumulative probabilities of neurological improvement, defined as a 1.0-point decrease in EDSS score sustained for ≥12 weeks, were estimated by Kaplan-Meier analysis. A Cox proportional hazards model identified associated baseline factors and examined treatment effects. RESULTS: Sustained improvement (as well as sustained worsening) in neurological disability was seen in AFFIRM patients. Sustained EDSS changes correlated well with quality of life measurements (SF36 and VAS). Natalizumab increased the cumulative probability of improvement over 2 years by 69% versus placebo (HR = 1.69; 95% CI 1.16-2.45; p = 0.006). Sensitivity analyses showed consistent benefits of natalizumab with variations in improvement magnitude and duration, and baseline disease activity. CONCLUSION: These analyses demonstrate that sustained EDSS improvement is an additional measure that is sensitive to treatment effects over 2 years and correlates with quality of life. Further research is warranted to validate its use as an MS study clinical outcome.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".