Are potentially clinically meaningful benefits misinterpreted in cardiovascular randomized trials? A systematic examination of statistical significance, clinical significance, and authors’ conclusions
Bibliographic record
Abstract
BACKGROUND: While journals and reporting guidelines recommend the presentation of confidence intervals, many authors adhere strictly to statistically significant testing. Our objective was to determine what proportions of not statistically significant (NSS) cardiovascular trials include potentially clinically meaningful effects in primary outcomes and if these are associated with authors' conclusions. METHODS: Cardiovascular studies published in six high-impact journals between 1 January 2010 and 31 December 2014 were identified via PubMed. Two independent reviewers selected trials with major adverse cardiovascular events (stroke, myocardial infarction, or cardiovascular death) as primary outcomes and extracted data on trial characteristics, quality, and primary outcome. Potentially clinically meaningful effects were defined broadly as a relative risk point estimate ≤0.94 (based on the effects of ezetimibe) and/or a lower confidence interval ≤0.75 (based on the effects of statins). RESULTS: We identified 127 randomized trial comparisons from 3200 articles. The primary outcomes were statistically significant (SS) favoring treatment in 21% (27/127), NSS in 72% (92/127), and SS favoring control in 6% (8/127). In 61% of NSS trials (56/92), the point estimate and/or lower confidence interval included potentially meaningful effects. Both point estimate and confidence interval included potentially meaningful effects in 67% of trials (12/18) in which authors' concluded that treatment was superior, in 28% (16/58) with a neutral conclusion, and in 6% (1/16) in which authors' concluded that control was superior. In a sensitivity analysis, 26% of NSS trials would include potential meaningful effects with relative risk thresholds of point estimate ≤0.85 and/or a lower confidence interval ≤0.65. CONCLUSIONS: Point estimates and/or confidence intervals included potentially clinically meaningful effects in up to 61% of NSS cardiovascular trials. Authors' conclusions often reflect potentially meaningful results of NSS cardiovascular trials. Given the frequency of potentially clinical meaningful effects in NSS trials, authors should be encouraged to continue to look beyond significance testing to a broader interpretation of trial results.
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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 | 0.690 | 0.903 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.014 |
| Bibliometrics | 0.045 | 0.034 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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, 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".