Cost–effectiveness of ticagrelor in patients with type 2 diabetes and coronary artery disease: a European economic evaluation of the THEMIS trial
Bibliographic record
Abstract
AIMS: To conduct a health economic evaluation of ticagrelor in patients with type 2 diabetes and coronary artery disease (CAD) from a multinational payer perspective. Cost-effectiveness and cost-utility of ticagrelor were evaluated in the overall effect of Ticagrelor on Health Outcomes in Diabetes Mellitus Patients Intervention Study (THEMIS) trial population and in the predefined patient group with prior percutaneous coronary intervention. METHODS AND RESULTS: A Markov model was developed to extrapolate patient outcomes over a lifetime horizon. The primary outcome was incremental cost-effectiveness ratios (ICERs), which were compared with conventional willingness-to-pay thresholds [€47 000/quality-adjusted life-year (QALY) in Sweden and €30 000/QALY in other countries].Treatment with ticagrelor resulted in QALY gains of up to 0.045 in the overall population and 0.099 in patients with percutaneous coronary intervention (PCI). Increased costs and benefits translated to ICERs ranged between €27 894 and €42 252/QALY across Sweden, Germany, Italy, and Spain in the overall population. In patients with prior PCI, estimated ICERs improved to €18 449, €20 632, €20 233, and €13 228/QALY in Sweden, Germany, Italy, and Spain, respectively, driven by higher event rates and treatment benefit. CONCLUSION: Based on THEMIS results, ticagrelor plus aspirin compared with aspirin alone may be cost-effective in some European countries in patients with T2DM and CAD and no prior myocardial infarction (MI) or stroke. Additionally, ticagrelor is likely to be cost-effective across European countries in patients with a history of PCI.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| 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) | 0.002 | 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".