Applying novel methods to assess clinical outcomes: insights from the TRILOGY ACS trial
Bibliographic record
Abstract
AIMS: Several methods provide new insights into understanding clinical trial composite endpoints, using both conventional and novel methods. The TRILOGY ACS trial is used as a contemporary example to prospectively compare these methods side by side. METHODS AND RESULTS: The traditional time-to-first-event, Andersen-Gill recurrent events method, win ratio, and a weighted composite endpoint (WCE) are compared using the randomized, active-control TRILOGY ACS trial. This trial had a neutral result and randomized 9326 patients managed without coronary revascularization within 10 days of their acute coronary syndrome to receive either prasugrel or clopidogrel and followed them for up to 30 months. The traditional composite, win ratio, and WCE demonstrated no significant survival advantage for prasugrel, whereas the Andersen-Gill method demonstrated a statistical advantage for prasugrel [hazard ratio (HR), 0.86 (95% CI, 0.72-0.97)]. The traditional composite used 73% of total patient events; 40% of these were derived from the death events. The win ratio used 66% of total events; deaths comprised 57% of these. Both Andersen-Gill and WCE methods used all events in all participants; however, with the Andersen-Gill method, death comprised 41% of the proportion of events, whereas with the WCE method, death comprised 64% of events. CONCLUSION: This study addresses the relative efficiency of various methods for assessing clinical trial events comprising the composite endpoint. The methods accounting for all events, in particular those incorporating their clinical relevance, appear most advantageous, and may be useful in interpreting future trials. This clinical and statistical advantage is especially evident with long-term follow-up where multiple non-fatal events are more common. CLINICAL TRIAL REGISTRATION: NCT00699998.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".