Modelling the Helsinki Heart Study by means of risk equations obtained from the PROCAM Study and the Framingham Heart Study.

Data from the Prospective Cardiovascular Münster (PROCAM) study have been used to develop a mathematical model that accurately predicts the outcome of treatment in a primary prevention study (the Helsinki Heart Study). The PROCAM study identified 8 major risk factors for coronary heart disease: age, total plasma cholesterol level, plasma high density lipoprotein (HDL)-cholesterol level, systolic blood pressure, smoking, diabetes, angina pectoris, and a family history of myocardial infarction. A single risk factor such as total plasma cholesterol level is not sufficiently sensitive to identify individuals at high risk of coronary heart disease. The total cholesterol:HDL-cholesterol ratio is recommended for clinical use. On the basis of these data, a primary prevention strategy for coronary heart disease in West Germany has been proposed to optimise the cost-effectiveness of such treatment. Future research should focus on the identification of feasible and sensitive risk factors for coronary heart disease. Fibrinogen and apolipoproteins have already attracted interest in this regard but more definitive studies are required to confirm their role as risk factors for coronary heart disease.