Cost effectiveness of lowering cholesterol concentration with statins in patients with and without pre-existing coronary heart disease: Life table method applied to health authority population

Objectives-To estimate the cost effectiveness of statins in lowering serum cholesterol concentration in people at varying risk of fatal cardiovascular disease and to explore the implications of changing the criteria for intervention on cost and cost effectiveness for a purchasing authority. Design-A life table method was used to model the effect of treatment with a statin on survival over 10 years in men and women aged 45-64. The costs of intervention were estimated from the direct costs of treatment, offset by savings associated with a reduction in coronary angiographies, non-fatal myocardial infarctions, and revascularisation procedures. The robustness of the model to various assumptions was tested in a sensitivity analysis. Setting-Population of a typical district health authority. Main outcome measure-Cost per life year saved. Results-The average cost effectiveness of treating men aged 45-64 with no history of coronary heart disease and a cholesterol concentration >6,5 mmol/l for 10 years with a statin was pound 136 000 per life year saved. The average cost effectiveness for patients with pre-existing coronary heart disease and a cholesterol concentration >5.4 mmol/l was pound 32 000. These averages hide enormous differences in cost effectiveness between groups at different risk, ranging from pound 6000 per life year in men aged 55-64 who have had a myocardial infarction and whose cholesterol concentration is above 7.2 mmol/l to pound 361 000 per life year saved in women aged 45-54 with angina and a cholesterol concentration of 5.5-6.0 mmol/l. Conclusions-Lowering serum cholesterol concentration in patients with and without preexisting coronary heart disease is effective and safe, but treatment for all those in whom treatment is likely to be effective is not sustainable within current NHS resources. Data on cost effectiveness data should be taken into account when assessing who should be eligible for treatment.