High risk strategies for atherosclerosis

Calculating a person's chances of developing coronary heart disease (CHD) is not simple, as many risk factors interact in a complex fashion. Thus many markers, though significant in univariate comparisons, are no longer so when multivariate analysis is performed. Those factors contributing independently to risk can be identified only in prospective investigations such as the Münster Heart (PROCAM) or the Framingham studies. In the Münster Heart study, follow-up of middle-aged men for eight years identified the following nine independent risk variables: age, smoking history, personal history of angina pectoris, family history of myocardial infarction, systolic blood pressure, raised plasma low density lipoprotein cholesterol (LDL-C), low plasma high density lipoprotein cholesterol, raised fasting plasma triglyceride and presence of diabetes mellitus. These have been used to generate an algorithm for prediction of first coronary events which is available in interactive fashion on the internet'. Large trials have shown that lowering LDL-C reduces the risk of CHD, and diminishes CHD morbidity and mortality in persons without prior evidence of coronary atherosclerosis (primary prevention). This is even more the case in patients with such evidence (secondary prevention). It appears that lowering of LDL-C also reduces all-cause mortality in secondary prevention.