The cost-effectiveness of rivaroxaban with or without aspirin in the COMPASS trial
Bibliographic record
Abstract
AIMS: The Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) trial demonstrated that rivaroxaban 2.5 mg BID with aspirin 100 mg was more effective than aspirin 100 mg daily alone for the prevention of cardiovascular (CV) death, stroke, or myocardial infarction in patients with stable coronary artery disease (CAD) or peripheral artery disease (PAD). We aimed to examine the cost-effectiveness of rivaroxaban using patient-level data from the COMPASS trial. METHODS AND RESULTS: We performed an in-trial analysis and extrapolated our results for 33 years using a two-state Markov model with a 1-year cycle length. Hospitalization events, procedures, and study drugs were documented for patients. We applied country-specific (Canada, France, and Germany) direct healthcare system costs (in USD) to healthcare resources consumed by patients. Average cost per patient during the trial (mean follow-up of 23 months), quality-adjusted life years (QALYs), and lifetime cost-effectiveness were calculated. Costs of events and procedures were reduced with rivaroxaban 2.5 mg BID with aspirin. The addition of rivaroxaban 2.5 mg BID increased total costs for the combination group. Over a lifetime horizon (in trial +33 years), rivaroxaban plus aspirin was associated with 1.17 QALYs gained, yielding an incremental cost-effectiveness ratio (ICER) of $3946/QALY, $9962/QALY, and $10 264/QALY in Canada, France, and Germany, respectively. PAD and polyvascular disease subgroups had lower ICERs. CONCLUSION: Rivaroxaban 2.5 mg twice daily plus aspirin compared with aspirin alone reduces direct healthcare costs. After acquisition costs of rivaroxaban, the lifetime cost-effectiveness of 2.5 mg twice daily plus aspirin is highly cost-effective in Canada, France, and Germany.(COMPASS ClinicalTrials.gov identifier: NCT01776424).
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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 | 0.006 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".