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Background The burden of atherosclerosis has led to treatment prioritization on high-risk individuals without established cardiovascular disease based on risk estimates. We investigated the effects of biological variation in risk factors on risk estimate accuracy and whether current primary prevention screening (risk assessment) models correctly categorize patients.

Methods A population of 10 000 ‘perfect’ individuals with 100 simulants affected by biological and analytical variation for systolic blood pressure, total cholesterol, high-density lipoprotein-cholesterol was mathematically modelled. Coronary heart disease (CHD) risks were calculated using the Framingham study algorithm and the mathematical properties of the screening system were evaluated.

Results At internationally recommended 10-year CHD risk treatment threshold levels of 15, 20 and 30%, the 95% confidence intervals were ± 5.1, ± 6.0 and ± 6.9 …