Efficacy and Cost-Effectiveness of Dabigatran Etexilate Versus Warfarin in Atrial Fibrillation in Different Age Subgroups
Bibliographic record
Abstract
This study aims to estimate the cost-effectiveness of dabigatran 150 mg twice daily versus warfarin for stroke and systemic embolism risk reduction in patients with nonvalvular atrial fibrillation initiating treatment before age 75 (<75), at or after age 75 (≥ 75), and the overall population (All) from a US Medicare payer perspective. Clinical event rates by age cohort with dabigatran or warfarin for safety-on-treatment and intent-to-treat populations were estimated from Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY). An economic model was adapted using these data to evaluate the impact of starting age on clinical and economic outcomes. Costs were obtained from Medicare payment schedules and utilities from publications. Model outputs included event rates, costs, quality-adjusted life-years, and incremental cost-effectiveness ratios. The RE-LY analysis shows that the <75 cohort has lower rates of all events than the ≥ 75 cohort; versus warfarin, dabigatran performed better in main efficacy and safety in all age cohorts with the exception of extracranial hemorrhage in the ≥ 75 cohort. The clinical event costs avoided per patient for dabigatran were $1,100, $135, and $713 for cohorts <75, ≥ 75, and All, respectively. Extrapolating over a lifetime horizon, the model found that dabigatran resulted in lower rates of stroke and intracranial hemorrhage and higher rates for extracranial hemorrhage versus warfarin for all age cohorts. Lifetime quality-adjusted life-years and costs were higher for dabigatran than warfarin, resulting in incremental cost-effectiveness ratios of $52,773, $65,946, and $56,131 for cohorts <75, ≥ 75, and All, respectively. In conclusion, dabigatran was cost-effective versus warfarin in US patients with atrial fibrillation regardless of age of treatment initiation.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".