Abstract 19642: Consistent Benefit of Ticagrelor Both Early and Late in Patients With Prior MI in PEGASUS-TIMI 54
Bibliographic record
Abstract
Objectives: Ticagrelor reduced the risk of CV death, MI or stroke in stable patients with prior MI in PEGASUS-TIMI 54. We investigated the consistency of ticagrelor’s efficacy and safety over time and quantified the magnitude of benefit in patients who tolerated ticagrelor for the first year, analogous to the clinical situation of extending therapy in patients after 1 year. Methods: PEGASUS-TIMI 54 randomized pts with a prior MI (median 1.7 yrs prior to randomization) to ticagrelor 90 mg twice daily, ticagrelor 60 mg twice daily or placebo. The rate CVD/MI/stroke and TIMI major bleeding were analyzed for the pooled ticagrelor doses compared to placebo for the first year of observation and then as a landmark analysis beginning after the first year in all patients alive at that time point. Results: 21,162 patients were randomized and followed for a median of 33 months, with 29% of patients ≥5 yrs from their most recent MI by the end of the trial. The rate of CVD/MI/stroke in the placebo arm remained roughly constant over the trial at ∼3%/y. Ticagrelor significantly reduced CVD/MI/stroke both over the first year (HR 0.84, 95% CI 0.71-0.98, P=0.029, Figure Left) and after year one (HR 0.85, 95% CI 0.74-0.97, P=0.017, Figure Right), with the event curves continuing to diverge through the end of follow-up. TIMI Major bleeding was increased with ticagrelor within the first year (HR 3.46, 95% CI 2.07-5.77) but numerically less so after the first year (HR 2.06, 95% CI 1.43-2.96). When examining patients who successfully completed one year of treatment, continued ticagrelor significantly reduced CVD/MI/Stroke by over 20% over the following two years (HR 0.79, 95% CI 0.68-0.91). Conclusion: Patients with a history of MI remain at persistent risk for CVD/MI/Stroke over time. Ticagrelor reduces this risk during the first year as well as in the subsequent years of treatment, supporting prolonged therapy.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".