Current clinical practice prevention guidelines rely on estimates of the absolute risk for development of cardiovascular disease (CVD) or coronary heart disease (CHD) within 10 years, in order to match the intensity of therapy to the magnitude of risk. However, many individuals have low 10-year risks but elevated lifetime risks for CVD. The National Cholesterol Education Program's Adult Treatment Panel III (NCEP ATP-III) therefore recommends consideration of long-term and lifetime risks in decisions regarding drug therapy. To date, a limited number of studies performed in exclusively white cohorts have examined lifetime risks for CVD events. No data are available regarding lifetime risks for CVD among other ethnic groups. Lifetime risk methods estimate the absolute risk for development of a disease prior to dying, by accounting for the risk of developing the disease of interest as well as the risk for competing causes of death. Since both CVD incidence and competing cause of death are considered in lifetime risk estimation, lifetime risks for CVD may vary considerably between ethnic groups with differing risk factor burdens and diverse rates of death from non-CVD causes. We propose to generate and pool estimates from multiple large epidemiologic cohort studies to compare lifetime risks for CVD between different ethnicities. Among the cohorts to be included in the proposed study are the Atherosclerosis Risk in Communities, Framingham Heart, Honolulu Heart, Puerto Rico Heart Health, CARDIA, Cardiovascular Health, People's Gas, Western Electric, Chicago Heart Association Detection Project in Industry, and Women's Health Initiative Observational Studies, MRFIT screenees, and others, comprising over 500,000 individuals. The resulting data on lifetime risks for CVD will be useful in estimating the population burden of CVD now and in the future, in comparing lifetime risks for CVD and other common diseases within and between race/ethnic groups, and in enhancing risk communication, and they have the potential to help identify new populations of patients at risk for CVD. This application represents a novel approach to analyzing existing data that is likely to yield substantial new insights into the epidemiology of CVD among non-white ethnic groups. ?
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