Safety reporting quality in multiple sclerosis clinical trials: A review of phase III clinical trials included in FDA approval of disease-modifying treatments
Bibliographic record
Abstract
Background: Evaluating safety of emerging interventions is important in clinical trials. To support reporting of safety outcomes, a harms extension of the Consolidated Standards of Reporting Trial (CONSORT) guidelines was published in 2004. Objective: To examine safety reporting in pivotal trials of disease-modifying therapies (DMTs) in patients with multiple sclerosis (MS). Methods: Published phase III clinical trials from 1995 to 2022 included in FDA approval material for MS DMTs were compiled and reviewed by two independent examiners. Criteria derived from the CONSORT harms extension were used to evaluate safety reporting. Linear regression was applied to examine associations between quality of safety reporting and study level factors. Results: = 0.005) were associated with higher quality reporting. Items related to laboratory-defined toxicity and defining adverse events were among reporting items notably lacking (present in 53% and 40% of publications, respectively). Conclusion: While the reporting of phase III clinical trials for DMTs for the treatment of MS has improved with time, there remain gaps and opportunities for further improvement.
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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 | 0.215 | 0.348 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".