Assessing disability progression with the Multiple Sclerosis Functional Composite
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The initial Multiple Sclerosis Functional Composite (MSFC) proposal was a three-part composite of quantitative measures of ambulation, upper extremity function, and cognitive function expressed as a single composite Z-score. However, the clinical meaning of an MSFC Z-score change is not obvious. This study instead used MSFC component data to define a patient-specific disease progression event. OBJECTIVE: Evaluate a new method for analyzing disability progression using the MSFC. METHODS: MSFC progression was defined as worsening from baseline on scores of at least one MSFC component by 20% (MSFC Progression-20) or 15% (MSFC Progression-15), sustained for >or=3 months. Progression rates were determined using data from natalizumab clinical studies (Natalizumab Safety and Efficacy in Relapsing Remitting Multiple Sclerosis [AFFIRM] and Safety and Efficacy of Natalizumab in Combination With Interferon Beta-1a in Patients With Relapsing Remitting Multiple Sclerosis [SENTINEL]). Correlations between MSFC progression and other clinical measures were determined, as was sensitivity to treatment effects. RESULTS: Substantial numbers of patients met MSFC progression criteria, with MSFC Progression-15 being more sensitive than MSFC Progression-20, at both 1 and 2 years. MSFC Progression-20 and MSFC Progression-15 were related significantly to Expanded Disability Status Scale (EDSS) score change, relapse rate, and the SF-36 Physical Component Summary (PCS) score change. MSFC Progression-20 and MSFC Progression-15 at 1 year were predictive of EDSS progression at 2 years. Both MSFC progression end points demonstrated treatment effects in AFFIRM, and results were replicated in SENTINEL. CONCLUSION: MSFC Progression-20 and MSFC Progression-15 are sensitive measures of disability progression; correlate with EDSS, relapse rates, and SF-36 PCS; and are capable of demonstrating therapeutic effects in randomized, controlled clinical studies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it