Cardiovascular disease risk prediction in the HIV outpatient study

Angela M. Thompson-Paul*, Kenneth A. Lichtenstein, Carl Armon, Frank J. Palella, Jacek Skarbinski, Joan S. Chmiel, Rachel Hart, Stanley C. Wei, Fleetwood Loustalot, John T. Brooks, Kate Buchacz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

100 Scopus citations


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 (D:A:D) 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 D:A:D 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 D:A:D 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.

Original languageEnglish (US)
Pages (from-to)1508-1516
Number of pages9
JournalClinical Infectious Diseases
Issue number11
StatePublished - Dec 1 2016


  • Cardiovascular disease
  • HIV
  • Risk prediction

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases


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