Can the functional assessment of multiple sclerosis adapt to changing needs? A psychometric validation in patients with clinically isolated syndrome and early relapsing–remitting multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: The Functional Assessment of Multiple Sclerosis (FAMS) is widely used in clinical trial programmes; however, it was developed before the rise in trials targeted at early stage multiple sclerosis (MS) and clinically isolated syndrome (CIS). OBJECTIVE: The aim of this study was to assess the psychometric properties of the FAMS within two clinically distinct populations, CIS and early relapsing-remitting MS (RRMS), and discern the appropriateness of the FAMS within these populations. METHODS: Secondary analysis was conducted on FAMS data from two clinical trials assessing interferon beta-1b in early RRMS and CIS. The statistical analysis assessed the scale acceptability, reliability, validity and responsiveness of the FAMS. Item response theory (IRT) was also conducted on the early RRMS sample in order to assess how well the FAMS discriminated amongst individuals with less severe MS. RESULTS: Results from both trials demonstrated an improvement in the FAMS psychometric properties with increased baseline disease severity. However, high ceiling effects were evident amongst less severe patients, and there was an overall lack of responsiveness to improvement and poor construct validity. IRT also demonstrated its lack of discrimination/sensitivity in early RRMS. CONCLUSIONS: In trials involving patients with early stage RRMS and CIS, modifications to the FAMS based on a qualitative assessment of its content validity in these populations would be required in order to potentially improve the FAMS psychometric properties and sensitivity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| 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".