Cost-effectiveness of the use of low- and high-potency statins in people at low cardiovascular risk
Bibliographic record
Abstract
BACKGROUND: Although statins have been shown to reduce the risk of cardiovascular events in patients at low cardiovascular risk, their absolute benefit is small in the short term, which may adversely affect cost-effectiveness. We sought to determine the long-term cost-effectiveness (beyond the duration of clinical trials) of low- and high-potency statins in patients at low cardiovascular risk and to estimate the impact on Canada's publicly funded health care system. METHODS: Using Markov modelling, we performed a cost-utility analysis in which we compared low-potency statins (fluvastatin, lovastatin, pravastatin and simvastatin) and high-potency statins (atorvastatin and rosuvastatin) with no statins in a simulated cohort of low-risk patients over a lifetime horizon. Model outcomes included costs (in 2010 Canadian dollars), quality-adjusted life-years (QALYs) gained and the cost per QALY gained. RESULTS: Over a lifetime horizon, the cost of managing a patient at low cardiovascular risk was estimated to be about $10,100 without statins, $15,200 with low-potency statins and $16,400 with high-potency statins. The cost per QALY gained with high-potency statins (v. no statins) was $21 300; the use of low-potency statins was not considered economically attractive. These results were robust to sensitivity analyses, although their use became economically unattractive when the duration of benefit from statin use was assumed to be less than 10 years. INTERPRETATION: Use of high-potency statins in patients at low cardiovascular risk was associated with a cost per QALY gained that was economically attractive by current standards, assuming that the benefit from statin use would continue for at least 10 years. However, the overall expenditure on statins would be substantial, and the ramifications of this practice should be carefully considered by policy-makers.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".