Cost-Effectiveness of Colchicine for Recurrent Cardiovascular Events
Bibliographic record
Abstract
Background: Colchicine is an anti-inflammatory therapy with a low associated cost that has been shown in 2 large studies to reduce cardiovascular (CV) events, but its use is associated with side effects. The main objective for this analysis is to determine whether colchicine therapy is cost-effective for the prevention of recurrent CV events in patients who have suffered a myocardial infarction (MI). Methods: A decision model was developed to estimate the healthcare costs in Canadian dollars and the clinical outcomes among patients who have suffered an MI and are treated with colchicine. Probabilistic Markov modelling was used in combination with Monte Carlo simulation to derive expected lifetime costs and quality-adjusted life-years, which permitted the calculation of incremental cost-effectiveness ratios. Models were derived for both short-term (20 months) and long-term (lifelong) colchicine use in this population. Results: Long-term colchicine use was dominant over standard of care, with lower average lifetime costs per patient (CAD$91,552.80 vs $97,085.84) and a higher average number of quality-adjusted life-years per patient (19.92 vs 19.80). Short-term colchicine use also dominated over standard of care. Results were consistent over a range of scenario analyses. Conclusions: Based on 2 large randomized controlled trials, treatment of patients post-MI with colchicine appears cost-effective, compared to the standard of care at the current price. Based on these studies and currently accepted willingness-to-pay thresholds in Canada, healthcare payers could consider funding long-term colchicine therapy for CV secondary prevention while we await results from ongoing trials.
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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".