2180Estimating individual lifetime benefit and bleeding risk of adding rivaroxaban to aspirin for patients with stable cardiovascular disease: results from the COMPASS trial
Bibliographic record
Abstract
Abstract Background The Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) trial has demonstrated that adding low-dose rivaroxaban to aspirin in patients with stable atherosclerotic disease on average reduces recurrence of cardiovascular disease (CVD) events, but increases the risk of major bleeding. For clinical practice, it is important to be able to weigh the absolute benefit from the intervention in terms of lower cardiovascular risk against the absolute increase in risk for major bleeding. Purpose The aim of this study was to estimate the individual lifetime benefit and harm of adding low-dose rivaroxaban to aspirin in patients with stable cardiovascular disease by predicting individual months free from CVD events gained and individual months free from major bleeding lost. Methods Analyses were based on data of patients with established CVD in the COMPASS trial (n=27,390) and SMART prospective cohort study (n=8,139). The externally validated lifetime SMART-REACH model for recurrent CVD was used to predict life expectancy free of stroke and myocardial infarction, based on the following predictors: sex, current smoking, diabetes mellitus, systolic blood pressure, total cholesterol, creatinine, number of locations of CVD, history of atrial fibrillation, and history of congestive heart failure. A new Fine & Gray competing-risk adjusted Cox proportional hazard model was derived in the COMPASS study population for prediction of life expectancy free from major bleeding, including the same predictors as the SMART-REACH model and additionally ethnicity, geographical region, and history of bleeding requiring transfusion. These lifetime estimates were then combined with hazard ratios from the COMPASS trial to estimate lifetime treatment effects from adding low-dose rivaroxaban to aspirin, expressed in terms of 1) months free from stroke or myocardial infarction gained, and 2) months free from major bleeding lost. Results External goodness-of-fit of the SMART-REACH model in the COMPASS study was sufficient. The newly developed major bleeding risk model also showed sufficient external goodness-of-fit in the SMART cohort. The median predicted individual gain in life-expectancy free of stroke or MI from added low-dose rivaroxaban was 16 months (range 1–48 months), while the median predicted individualized lifetime lost in terms of major bleeding was 2 months (range 0–20 months) (Figure 1A). Predicted benefit was higher than predicted harm in more than 90% of the study population. An interactive calculator for use in clinical practice will be made available (example in figure 1B). Figure 1 Conclusions There is a wide distribution in lifetime gain and harm from adding low-dose rivaroxaban to aspirin in individual patients with stable CVD. Using these lifetime models, benefits and bleeding risk can be weighed for and with each individual patient, to support treatment decision making in clinical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".