Canadian Cost-Effectiveness of Coronary Artery Calcium Screening Based on the Multi-Ethnic Study of Atherosclerosis
Bibliographic record
Abstract
Background: Cost-effectiveness of testing for coronary artery calcium (CAC) relative to other treatment strategies is not established in Canada. Objectives: The purpose of this study was to evaluate the cost-effectiveness of using CAC score-guided statin treatment compared with universal statin therapy among intermediate-risk, primary prevention patients eligible for statins. Methods: A state transition, microsimulation model used data from Canadian sources and the Multi-Ethnic Study of Atherosclerosis to simulate clinical and economic consequences of cardiovascular disease from a Canadian publicly funded health care system perspective. In the CAC score-guided treatment arm, statins were started when CAC ≥1. Outcome of interest was the incremental cost-effectiveness ratio at 5 and 10 years; an incremental cost-effectiveness ratio <$50,000 per quality-adjusted life year (QALY) gained was considered cost-effective. Sensitivity analyses examined uncertainty in model parameters. Results: Compared with universal statin treatment at 5 and 10 years, CAC score-guided statin treatment was projected to increase mean costs by $326 (95% CI: $325-$326) and $172 (95% CI: $169-$175), increase mean QALYs by 0.01 (95% CI: 0.01-0.01) and 0.02 (95% CI: 0.02-0.02), and cost $54,492 (95% CI: $52,342-$56,816) and $8,118 (95% CI: $7,968-$8,279) per QALY gained, respectively. The model was most sensitive to statin cost, CAC testing cost, adherence to statin monitoring, and disutility associated with daily statin use. At 5 years, CAC score-guided statin treatment was cost-effective when CAC test costs ranged from $80 to $160 in different scenarios. Conclusions: CAC score-guided statin initiation in comparison to universal statin treatment was borderline cost-neutral at 5 years and cost-effective at 10 years in statin-eligible Canadian patients at intermediate cardiovascular disease risk.
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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 | 0.000 | 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".