Validation of an Atrial Fibrillation Risk Algorithm in Whites and African Americans

The prevalence and incidence of atrial fibrillation (AF) have been increasing over the last several decades.1,2 The improved assessment of risk for incident AF was formulated as one of the major goals of a recently convened National Heart, Lung, and Blood Institute workshop.3 A risk algorithm based on readily available clinical variables for 10-year incidence of AF in Framingham Heart Study (FHS) participants (http://www.framinghamheartstudy.org/risk/index.html) has been published.4 Transportability to independent cohorts and other ethnicities with different incidence rates and distributions of risk factors has to be shown before general recommendations for the use of the risk algorithm can be given. In particular, in African Americans (AA), a paradoxically low prevalence of AF has consistently been reported despite a high risk factor burden.5,6 Thus, it is important to understand how the classical risk factors for AF combined in a risk prediction algorithm are associated with risk in African Americans. We tested a risk algorithm for AF incidence developed in the Framingham Heart Study in two large, independent community-based cohorts from the US (Cardiovascular Health Study, CHS) and Europe (Age, Gene/Environment Susceptibility-Reykjavik Study, AGES). In CHS we had the opportunity to examine risk factor prevalence and association with incident AF in whites and AA. An accurate risk assessment tool is necessary to address the increasing burden of AF in the community by facilitating the identification of individuals at increased absolute risk to potentially target for intervention trials. With the current project we intended to take the second step of a risk algorithm implementation: the validation of the risk function in samples independent of the derivation cohort.