Inadequate Reporting of Cointerventions, Other Methodological Factors, and Treatment Estimates in Cardiovascular Trials: A Meta-Epidemiological Study
Bibliographic record
Abstract
Objective To assess how inadequate reporting of cointerventions influences estimated treatment effects in recent cardiovascular trials. Methods Medline/Embase were systematically searched from January 1, 2011 to July 1, 2021 for trials evaluating pharmacologic interventions on clinical cardiovascular outcomes published in 5 high-impact journals. Information on adequate vs inadequate reporting of cointerventions, blinding, risk of bias due to deviations of intended interventions (low vs high/some concerns), funding (nonindustry vs industry), design (superiority vs noninferiority), and results were assessed by 2 reviewers. The association with effect sizes was assessed using meta-regression random-effect analysis, expressed as ratios of odds ratios (ROR). RORs of >1.0 indicated that trials with the methodological factor pointing to lower quality report larger treatment estimates. Results In total, 164 trials were included. Of the 164 trials, 124 (74%) did not adequately report cointerventions; 89 of the 164 trials (54%) provided no information regarding cointerventions, and 70 of the 164 (43%) were at risk of bias due to inadequate blinding. Moreover, 86 of the 164 (53%) were at risk of bias due to deviation of intended interventions. Of the 164 trials, 144 (88%) were funded by the industries. Trials with inadequate reporting of cointerventions had larger treatment estimates for the primary end point (ROR, 1.08; 95% CI, 1.01-1.15; I 2 =0%). No significant association with results for blinding (ROR, 0.97; 95% CI, 0.91-1.03; I 2 =66%), deviation of intended interventions (ROR, 0.98; 95% CI, 0.92-1.04; I 2 =0%), or funding (ROR, 1.01; 95% CI, 0.93-1.09; I 2 =0%) was found. Conclusion We conclude that trials with inadequate reporting of cointerventions showed larger treatment effect estimates, potentially indicating overestimation of therapeutic benefit. Trial Registration Prospero Identifier: CRD42017072522
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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 | MetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad) Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | MetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | 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 | 0.379 | 0.590 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.022 | 0.057 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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, 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".