Context The Framingham Heart Study produced sex-specific coronary heart disease
(CHD) prediction functions for assessing risk of developing incident CHD in
a white middle-class population. Concern exists regarding whether these functions
can be generalized to other populations.
Objective To test the validity and transportability of the Framingham CHD prediction
functions per a National Heart, Lung, and Blood Institute workshop organized
for this purpose.
Design, Setting, and Subjects Sex-specific CHD functions were derived from Framingham data for prediction
of coronary death and myocardial infarction. These functions were applied
to 6 prospectively studied, ethnically diverse cohorts (n = 23 424),
including whites, blacks, Native Americans, Japanese American men, and Hispanic
men: the Atherosclerosis Risk in Communities Study (1987-1988), Physicians'
Health Study (1982), Honolulu Heart Program (1980-1982), Puerto Rico Heart
Health Program (1965-1968), Strong Heart Study (1989-1991), and Cardiovascular
Health Study (1989-1990).
Main Outcome Measures The performance, or ability to accurately predict CHD risk, of the Framingham
functions compared with the performance of risk functions developed specifically
from the individual cohorts' data. Comparisons included evaluation of the
equality of relative risks for standard CHD risk factors, discrimination,
Results For white men and women and for black men and women the Framingham functions
performed reasonably well for prediction of CHD events within 5 years of follow-up.
Among Japanese American and Hispanic men and Native American women, the Framingham
functions systematically overestimated the risk of 5-year CHD events. After
recalibration, taking into account different prevalences of risk factors and
underlying rates of developing CHD, the Framingham functions worked well in
Conclusions The sex-specific Framingham CHD prediction functions perform well among
whites and blacks in different settings and can be applied to other ethnic
groups after recalibration for differing prevalences of risk factors and underlying
rates of CHD events.