Health economic evaluation of rivaroxaban in the treatment of patients with chronic coronary artery disease or peripheral artery disease
Bibliographic record
Abstract
AIMS: In the COMPASS trial, rivaroxaban 2.5 mg twice daily (bid) plus acetylsalicylic acid (ASA) 100 mg once daily (od) performed better than ASA 100 mg od alone in reducing the rate of cardiovascular disease, stroke, or myocardial infarction (MI) in patients with coronary artery disease (CAD) and peripheral artery disease (PAD). A Markov model was developed to assess the cost-effectiveness of rivaroxaban plus ASA vs. ASA alone over a lifetime horizon, from the UK National Health System perspective. METHODS AND RESULTS: The base case analysis assumed that patients entered the model in the event-free health state, with the possibility to experience ≤2 events, transitioning every three-month cycle, through acute and post-acute health states of MI, ischaemic stroke (IS), or intracranial haemorrhage (ICH), and death. Costs, quality-adjusted life-years (QALYs), life years-all discounted at 3.5%-and incremental cost-effectiveness ratios (ICERs) were calculated. Deterministic and probabilistic sensitivity analyses were conducted, as well as scenario analyses. In the model, patients on rivaroxaban plus ASA lived for an average of 14.0 years with no IS/MI/ICH, and gained 9.7 QALYs at a cost of £13 947, while those receiving ASA alone lived for an average of 12.7 years and gained 9.3 QALYs at a cost of £8126. The ICER was £16 360 per QALY. This treatment was cost-effective in 98% of 5000 iterations at a willingness-to-pay threshold of £30 000 per QALY. CONCLUSION: This Markov model suggests that rivaroxaban 2.5 mg bid plus ASA is a cost-effective alternative to ASA alone in patients with chronic CAD or PAD.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".