Evaluation of early percutaneous coronary intervention vs. standard therapy after fibrinolysis for ST-segment elevation myocardial infarction: contribution of weighting the composite endpoint
Bibliographic record
Abstract
AIMS: The selection of optimal endpoints for cardiovascular clinical trials continues to be challenging. We examined an alternative interpretation of a series of trials when the individual event severity is considered. METHODS AND RESULTS: We analysed three contemporary myocardial infarction (MI) trials of early percutaneous coronary intervention after fibrinolysis, using a weighted composite method. This method allows the examination of the heterogeneity in the direction and magnitude of component endpoints, and multiple events (vs. first event). We incorporated a physician-assessed severity of each component endpoint in all patients for the five-item composite in the largest study, Trial of Routine Angioplasty and Stenting after Fibrinolysis to Enhance Reperfusion in Acute Myocardial Infarction (TRANSFER-AMI), which enrolled 1059 ST-elevation MI patients. The traditional approach yielded event-free survival probabilities of 0.89 [95% confidence interval (CI) 0.86-0.91] for the early invasive arm and 0.83 (95% CI 0.79-0.86) for the standard care arm (P = 0.004). After accounting for the clinician-investigator-determined weights, the effective survival probabilities were 0.93 (95% CI 0.91-0.95) for the early invasive arm and 0.93 (95% CI 0.90-0.95) with no significant difference (P = 0.54). The same pattern was observed in the three-trial cohort using a four-item composite with an observed improvement in event-free survival outcomes (P = 0.01), which was no longer apparent after the severity weights were considered (P = 0.44). CONCLUSION: This analysis highlights the importance of considering the relative severity and multiple events in the evaluation of a clinical trial.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".