Aspirin in primary prevention are based on the risk estimations provided by the FRS. Most risk scores were developed in white middle-aged populations. Thus, it is uncertain whether risk estimates based on these scores can be generalized to the elderly. The FRS, for example, was developed in a white middle-aged population with a mean age of 49 years and included persons as young as 30 and none older than 74. Actual risk prediction with FRS might perform less well in older adults compared to middle-aged adults, and some traditional risk factors have weaker associations with CHD risk in the elderly; for example, total and LDL-cholesterol are strong cardiovascular risk factors in middle-aged but not in older adults. As it remains unclear whether and how CHD risk prediction might be improved in the growing population of elderly to facilitate primary prevention strategies, we aimed to compare the prognostic performance. During 8-year follow-up, we assessed incident CHD events and mortality among Halothane Participants without overt CVD at baseline. Using algorithms mirroring those of the Cardiovascular Health Study, diagnoses and cause of death were adjudicated until 2006�C2007 based on interview, review of all hospital records, death certificates, and other Acetrizoic acid documents by a panel of clinicians. CHD events included nonfatal myocardial infarction or coronary death, and hospitalization for angina or revascularization. The FRS predicts 10-year CHD risk based on a Cox model estimated using data from the Framingham Heart Study. The Framingham cohort included 5345 subjects aged 30�C74 years at the time of their examination in 1971�C1974. For this analysis, we used the sex-specific Framingham equations of Wilson, because they include diabetes, a strong independent CHD risk factor. This FRS Cox model includes age, total and HDL cholesterol, blood pressure, diabetes, and smoking status. In this study, we compared the prognostic performance of the FRS, directly and after recalibration, with functions entirely derived from the Health ABC cohort, similar to previous studies. Analyses were stratified by gender. We first estimated the FRS using regression coefficient estimates and values of the risk factor means reported by Wilson. To account for the shorter follow-up in the Health ABC study and to avoid extrapolation beyond the range of the data, we examined 7.5-year risk and adapted accordingly the estimated baseline survival function used in computing the FRS. Participants who died from non-CHD death were censored at the time of death. We then examined whether the predictive performance of the FRS could be improved with recalibration or with refitting model coefficients. For the recalibrated version of the FRS, we reestimated predicted risks for Health ABC by retaining the original coefficient estimates reported by Wilson but adapted the risk factor means to the present cohort and the Kaplan Meier estimate of the baseline survival function of Health ABC data.