Cost-effectiveness of dabigatran etexilate for the prevention of stroke and systemic embolism in atrial fibrillation: A Canadian payer perspective
Bibliographic record
Abstract
Oral dabigatran etexilate is indicated for the prevention of stroke and systemic embolism in patients with atrial fibrillation (AF) in whom anticoagulation is appropriate. Based on the RE-LY study we investigated the cost-effectiveness of Health Canada approved dabigatran etexilate dosing (150 mg bid for patients <80 years, 110 mg bid for patients ≥80 years) versus warfarin and "real-world" prescribing (i.e. warfarin, aspirin, or no treatment in a cohort of warfarin-eligible patients) from a Canadian payer perspective. A Markov model simulated AF patients at moderate to high risk of stroke while tracking clinical events [primary and recurrent ischaemic strokes, systemic embolism, transient ischaemic attack, haemorrhage (intracranial, extracranial, and minor), acute myocardial infarction and death] and resulting functional disability. Acute event costs and resulting long-term follow-up costs incurred by disabled stroke survivors were based on a Canadian prospective study, published literature, and national statistics. Clinical events, summarized as events per 100 patient-years, quality-adjusted life years (QALYs), total costs, and incremental cost effectiveness ratios (ICER) were calculated. Over a lifetime, dabigatran etexilate treated patients experienced fewer intracranial haemorrhages (0.49 dabigatran etexilate vs. 1.13 warfarin vs. 1.05 "real-world" prescribing) and fewer ischaemic strokes (4.40 dabigatran etexilate vs. 4.66 warfarin vs. 5.16 "real-world" prescribing) per 100 patient-years. The ICER of dabigatran etexilate was $10,440/QALY versus warfarin and $3,962/QALY versus "real-world" prescribing. This study demonstrates that dabigatran etexilate is a highly cost-effective alternative to current care for the prevention of stroke and systemic embolism among Canadian AF patients.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".