PURPOSE: To examine the effect of correcting coronary heart disease (CHD) risk factors for long-term within-person variation on CHD risk. METHODS: By using 5533 men and 7301 women from the Atherosclerosis Risk in Communities (ARIC) study, we compared models incorporating risk factors measured at a single visit and models incorporating additional measurements for systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol taken 3 years before baseline. RESULTS: The largest change away from null was observed for systolic blood pressure, ie, hazard ratio (HR) 1.38 to 1.69 (+81%) in women and HR 1.26 to 1.41 (+56%) in men. HRs also decreased for age (-32% in women, -9% in men), race (-67% in women), the presence of diabetes (-13% in men and women), and medication use for hypertension (-27% in women, -26% in men) and cholesterol (-97% in women, HR 1.06-0.93 in men). The area under the ROC curve did not improve significantly in men or women, whereas reclassification was only significant in women (net reclassification improvement 5.4%, p = 0.016). CONCLUSIONS: Modeling long-term variation in CHD risk factors had a substantial impact on HR estimates, with new effect estimates further from the null for some risk factors and closer for others including age and medication use, but only improved risk classification in women.
PURPOSE: To examine the effect of correcting coronary heart disease (CHD) risk factors for long-term within-person variation on CHD risk. METHODS: By using 5533 men and 7301 women from the Atherosclerosis Risk in Communities (ARIC) study, we compared models incorporating risk factors measured at a single visit and models incorporating additional measurements for systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol taken 3 years before baseline. RESULTS: The largest change away from null was observed for systolic blood pressure, ie, hazard ratio (HR) 1.38 to 1.69 (+81%) in women and HR 1.26 to 1.41 (+56%) in men. HRs also decreased for age (-32% in women, -9% in men), race (-67% in women), the presence of diabetes (-13% in men and women), and medication use for hypertension (-27% in women, -26% in men) and cholesterol (-97% in women, HR 1.06-0.93 in men). The area under the ROC curve did not improve significantly in men or women, whereas reclassification was only significant in women (net reclassification improvement 5.4%, p = 0.016). CONCLUSIONS: Modeling long-term variation in CHD risk factors had a substantial impact on HR estimates, with new effect estimates further from the null for some risk factors and closer for others including age and medication use, but only improved risk classification in women.
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