Evaluating prospective study registration and result reporting of trials conducted in Canada from 2009 to 2019
Bibliographic record
Abstract
Adherence to study registration and reporting best practices is vital to fostering evidence-based medicine. All registered clinical trials on ClinicalTrials.gov conducted in Canada as of 2009 and completed by 2019 were identified. A cross-sectional analysis of those trials assessed prospective registration, subsequent result reporting in the registry, and subsequent publication of study findings. The lead sponsor, phase of study, clinical trial site location, total patient enrollment, number of arms, type of masking, type of allocation, year of completion, and patient demographics were examined as potential effect modifiers to these best practices. A total of 6720 trials were identified. From 2009 to 2019, 59% ( n = 3,967) of them were registered prospectively, and 32% ( n = 2138) had neither their results reported nor their findings published. Of the 3763 trials conducted exclusively in Canada, 3% ( n = 123) met all three criteria of prospective registration, reporting in the registry, and publishing findings. Overall, the odds of having adherence to all three practices concurrently in Canadian trials decrease by 95% when compared with international trials. Canadian clinical trials substantially lacked adherence to study registration and reporting best practices. Knowledge of this widespread non-compliance should motivate stakeholders in the Canadian clinical trial ecosystem to address and continue to monitor this problem.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reporting · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | low |
| gpt | MetaresearchOpen science Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
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 | 0.578 | 0.776 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.023 | 0.050 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".