Risk prediction models for cardiovascular disease have been developed primarily among white men and women, with little validation in multi-ethnic populations. The overall aim of the current proposal is to validate existing Framingham and Reynolds risk scores, and to explore new predictive models for cardiovascular disease (CVD), including MI, stroke, and CVD mortality in the Women's Health Initiative Observational Study. An effcient case-cohort sample of 4000 women will be used, including 2000 cases spread across ethnic groups, and a subcohort of at least 2000 women frequency matched to the cases by race/ethnicity and 1 O-year age groups. This proposal will validate current models both overall and separately in subgroups defined by race/ethnicity. We wil fi new models in subpopulations separately, particularly Caucasian and African-American women, and wil fit models for CHD and stroke separately in the total cohort. Current risk prediction models contain blood-based biomarkers, but do not include measures of adiposity or physical activity. We will explore models without blood-based biomarkers, and compare these to models using such measures. We will also explore the contribution of new proposed biomarkers for risk prediction beyond those already included in the Framingham and Reynolds models, including lipoprotein-associated phospholipase A2 (Lp-PLA), tissue plasminogen activator (tPA antigen), and amino-terminal pro-B-type natriuretic peptide (proBNP), In addition, we will refine methods for the comparison of risk prediction models, including examining the statistical properties of clinical reclassification and its summary measures.
