Clopidogrel versus aspirin in patients with atherothrombosis: CAPRIE-based calculation of cost-effectiveness for Germany
Bibliographic record
Abstract
Objectives: To model the 2-year cost-effectiveness of secondary prevention with clopidogrel versus aspirin (acetylsalicylic acid) (ASS) in German patients with myocardial infarction (MI), ischaemic stroke (IS) or diagnosed with peripheral arterial disease (PAD), based on CAPRIE trial data and from the perspective of German third party payers (TPP).Methods: An existing Markov model was adapted to Germany by using German cost data. The model was extended by using different datasets for cardiovascular event survival times (Framingham vs. Saskatchewan health databases) and in two separate scenarios.Results: The treatment with clopidogrel leads to a reduction of 13.19 vascular events per 1000 patients, of which 2.21 are vascular deaths. The overall incremental costs for the 2-year management of atherothrombotic patients with clopidogrel instead of ASS are calculated to be about €1 241 440 per 1000 patients. The number of life-years saved (LYS) has been calculated as the difference in the number of life-years lost due to vascular death or events with ASS versus clopidogrel: it is 86.35 LYS when analysis is based on Framingham data and 66.07 LYS with Saskatchewan-based survival data. The incremental costs per LYS are €14 380 and €18 790, respectively. Cost-effectiveness is sensitive to changes in survival data, discounting and daily costs of clopidogrel, but stable against substantial (± 25%) changes in all other cost data.Conclusion: The findings for Germany are in line with published results for Belgium (€13 390 per LYS) and also with results for Italy (€17 500 per LYS), both based on Saskatchewan data, and with a French analysis based on Framingham data (€15 907 per LYS). Even if no officially accepted cost-effectiveness threshold exists for Germany at present, incremental cost-effectiveness results of less than €20 000 per LYS for the treatment with clopidogrel can be assumed to be acceptable for German third party payers.
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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".