Cardiovascular Disease Risk Prediction in the HIV Outpatient Study.

ABSTRACT

BACKGROUND: Cardiovascular disease (CVD) risk prediction tools are often applied to populations beyond those in which they were designed when validated tools for specific subpopulations are unavailable. METHODS: Using data from 2283 human immunodeficiency virus (HIV)-infected adults aged ≥18 years, who were active in the HIV Outpatient Study (HOPS), we assessed performance of 3 commonly used CVD prediction models developed for general populations Framingham general cardiovascular Risk Score (FRS), American College of Cardiology/American Heart Association Pooled Cohort equations (PCEs), and Systematic COronary Risk Evaluation (SCORE) high-risk equation, and 1 model developed in HIV-infected persons the Data Collection on Adverse Effects of Anti-HIV Drugs (DAD) study equation. C-statistics assessed model discrimination and the ratio of expected to observed events (E/O) and Hosmer-Lemeshow χ2 P value assessed calibration. RESULTS: From January 2002 through September 2013, 195 (8.5%) HOPS participants experienced an incident CVD event in 15 056 person-years. The FRS demonstrated moderate discrimination and was well calibrated (C-statistic 0.66, E/O 1.01, P = .89). The PCE and DAD risk equations demonstrated good discrimination but were less well calibrated (C-statistics 0.71 and 0.72 and E/O 0.88 and 0.80, respectively; P < .001 for both), whereas SCORE performed poorly (C-statistic 0.59, E/O 1.72; P = .48). CONCLUSIONS: Only the FRS accurately estimated risk of CVD events, while PCE and DAD underestimated risk. Although these models could potentially be used to rank US HIV-infected individuals at higher or lower risk for CVD, the models may fail to identify substantial numbers of HIV-infected persons with elevated CVD risk who could potentially benefit from additional medical treatment.