Investigating the Prevalence of Comorbidity in Multiple Sclerosis Clinical Trial Populations
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Comorbidity is common in multiple sclerosis (MS) with the most prevalent conditions being depression, anxiety, hypertension, and hyperlipidemia. Limited information regarding the representation of comorbidity status is available from phase III clinical trials in MS leading to concern about the potential underrepresentation of individuals with comorbidity in clinical trials. The objective was to estimate the prevalence of comorbidities in MS clinical trial populations. METHODS: statistic. RESULTS: = 93.2). Heterogeneity was high across trials. Older age and female participants were associated with increased number of comorbidities. Older individuals and male participants had a higher prevalence of hyperlipidemia, while older individuals and female participants had a higher prevalence of depression and anxiety. DISCUSSION: Individuals with comorbidities are included in clinical trials, although they may still be underrepresented compared with the general MS population. Given the comorbidity prevalence in the trial populations and studies suggesting an association of comorbidities with disease activity, comorbidity may influence outcomes in clinical trials.
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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 | 0.114 | 0.288 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".