Alirocumab Reduces Total Nonfatal Cardiovascular and Fatal Events
Bibliographic record
Abstract
BACKGROUND: The ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) trial compared alirocumab with placebo, added to high-intensity or maximum-tolerated statin treatment, after acute coronary syndrome (ACS) in 18,924 patients. Alirocumab reduced the first occurrence of the primary composite endpoint and was associated with fewer all-cause deaths. OBJECTIVES: This pre-specified analysis determined the extent to which alirocumab reduced total (first and subsequent) nonfatal cardiovascular events and all-cause deaths in ODYSSEY OUTCOMES. METHODS: Hazard functions for total nonfatal cardiovascular events (myocardial infarction, stroke, ischemia-driven coronary revascularization, and hospitalization for unstable angina or heart failure) and death were jointly estimated, linked by a shared frailty accounting for patient risk heterogeneity and correlated within-patient nonfatal events. An association parameter also quantified the strength of the linkage between risk of nonfatal events and death. The model provides accurate relative estimates of nonfatal event risk if nonfatal events are associated with increased risk for death. RESULTS: With 3,064 first and 5,425 total events, 190 fewer first and 385 fewer total nonfatal cardiovascular events or deaths were observed with alirocumab compared with placebo. Alirocumab reduced total nonfatal cardiovascular events (hazard ratio: 0.87; 95% confidence interval: 0.82 to 0.93) and death (hazard ratio: 0.83; 95% confidence interval: 0.71 to 0.97) in the presence of a strong association between nonfatal and fatal event risk. CONCLUSIONS: In patients with ACS, the total number of nonfatal cardiovascular events and deaths prevented with alirocumab was twice the number of first events prevented. Consequently, total event reduction is a more comprehensive metric to capture the totality of alirocumab clinical efficacy after ACS.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".