Mismatch of coronary risk and treatment intensity under the National Cholesterol Education Program guidelines

To assess the match between multifactorial risk of coronary heart disease (CHD) and treatment intensity under the National Cholesterol Education Program (NCEP) guidelines for primary prevention of CHD.

The multiple logistic regression equation from the Framingham Study was used to derive predicted risks for development of CHD over eight years of follow-up for different age-gender groupings, with serum total cholesterol (TC) values chosen in light of the NCEP cutoff points for both TC and low-density-lipoprotein cholesterol levels. Additional risk factors--hypertension, glucose intolerance, and smoking--were considered in combination for each of these values.

Controlling for the effects of age and gender, there is little difference in the ranges of absolute CHD risks for persons who would receive interventions of differing intensities (i.e., general dietary advice, dietary treatment, or drug therapy). Those who are candidates for drug treatment because of serum lipids alone are often at low levels of risk for the development of CHD when compared with those of the same age with lower TC values who have other risk factors. Discrepancies in CHD risk are wider still when age is also allowed to vary. Furthermore, in every age grouping, women with high TC levels (e.g., 6.9 mmol/L) and two other risk factors are eligible for drug treatment but have a CHD risk that is no higher, and often much lower, than that of males with one other risk factor and TC levels of 4.8 mmol/L or 5.7 mmol/L who are candidates for dietary advice or dietary therapy, respectively.

Inconsistencies exist in the NCEP guidelines such that persons at low risk for the development of CHD are offered more intensive interventions than are other who actually are at much higher risks, and vice versa. Women in particular tend to be overtreated, relative to men. These findings point out the difficulties of promulgating guidelines that will appropriately match risk to preventive interventions in a complex multifactorial disease.