Use of the Multiple Sclerosis Functional Composite as an Outcome Measure in a Phase 3 Clinical Trial
Bibliographic record
Abstract
BACKGROUND: The Multiple Sclerosis Functional Composite (MSFC) is a multidimensional clinical outcome measure that includes quantitative tests of leg function/ambulation (Timed 25-Foot Walk), arm function (9-Hole Peg Test), and cognitive function (Paced Auditory Serial Addition Test). The MSFC is the primary outcome measure in the ongoing multinational phase 3 trial of interferon beta-1a (Avonex) in patients with secondary progressive MS. OBJECTIVE: To assess the practice effects, reliability, and validity of the MSFC clinical outcome measure. DESIGN: Examining technicians underwent formal training using standardized materials. The MSFC was performed according to a standardized protocol. The 436 patients enrolled in the International Multiple Sclerosis Secondary Progressive Avonex Controlled Trial underwent 3 prebaseline MSFC testing sessions before randomization. RESULTS: Practice effects were evident initially for the MSFC but stabilized by the fourth administration. The Paced Auditory Serial Addition Test demonstrated the most prominent practice effects. The reliability of the MSFC was excellent, with an intraclass correlation coefficient for session 3 (final prebaseline session) vs session 4 (baseline) of 0.90. The MSFC at baseline correlated moderately strongly with the Kurtzke Expanded Disability Status Scale. Among the MSFC components, the Timed 25-Foot Walk correlated most closely. Correlations among the 3 MSFC components were weak, suggesting they assess distinct aspects of neurologic function in patients with MS. CONCLUSIONS: The MSFC demonstrated excellent intrarater reliability in this multinational phase 3 trial. Three prebaseline testing sessions were sufficient to compensate for practice effects. The pattern of correlations among the MSFC, its components, and the Kurtzke Expanded Disability Status Scale supported the validity of the MSFC.
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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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".