Integrating information from novel risk factors with calculated risks : the critical impact of risk factor prevalence

Abstract

Case vignette: a 60-year-old man visits his physician for assessment of his 10-year cardiovascular risk. On the basis of his systolic blood pressure, lipid profile, smoking status, and the fact that he is nondiabetic, the Framingham risk score estimates his risk to be 8%. The physician wonders if he could further specify the patients risk by performing an additional test like coronary calcium score or microalbuminuria (MA). For matters of convenience and costs he decides to test MA, which turns out positive. Assuming that MA has an invariable and exact relative risk (RR), independent from the aforementioned classical risk factors, of 2.0, what would this man’s estimated risk become?