On the use of a logistic risk score in predicting risk of coronary heart disease

Abstract

Many studies over the last 20 years have used logistic regression to model the relationship between the risk of developing coronary heart disease (CHD) and the levels of risk factors such as high blood pressure, high serum cholesterol, and cigarette smoking. Subsequently, several investigators have proposed the use of some of the published estimated logistic risk functions to predict risk in new populations. Because of great variation in definition of event, duration of follow-up, population characteristics, definition of risk variables, and selection of other variables in the logistic functions, direct use of such established functions would generally not have validity for the prediction of absolute risk levels. A review of fifteen of these studies indicates on the one hand generally similar results in direction and order of magnitude of effects of the major risk factors, confirming the importance of these risk factors of CHD. On the other hand the reviews indicate sufficient variation to suggest that extrapolation to new populations even to predict relative risk is not justified.