title: Predicting the risk of cardiovascular disease in HIV-infected patients: the data collection on adverse effects of anti-HIV drugs study.
abstract: OBJECTIVE
  HIV-infected patients receiving combination antiretroviral therapy may experience metabolic complications, potentially increasing their risk of cardiovascular diseases (CVDs). Furthermore, exposures to some antiretroviral drugs seem to be independently associated with increased CVD risk. We aimed to develop cardiovascular risk-assessment models tailored to HIV-infected patients.
  
  
  RESULTS
  Prospective multinational cohort study. The data set included 22,625 HIV-infected patients from 20 countries in Europe and Australia who were free of CVD at entry into the Data collection on Adverse Effects of Anti-HIV Drugs Study. Using cross-validation methods, separate models were developed to predict the risk of myocardial infarction, coronary heart disease, and a composite CVD endpoint. Model performance was compared with the Framingham score. The models included age, sex, systolic blood pressure, smoking status, family history of CVD, diabetes, total cholesterol, HDL cholesterol and indinavir, lopinavir/r and abacavir exposure. The models performed well with area under the receiver operator curve statistics of 0.783 (range 0.642-0.820) for myocardial infarction, 0.776 (0.670-0.818) for coronary heart disease and 0.769 (0.695-0.824) for CVD. The models estimated more accurately the outcomes in the subgroups than the Framingham score.
  
  
  CONCLUSIONS
  Risk equations developed from a population of HIV-infected patients, incorporating routinely collected cardiovascular risk parameters and exposure to individual antiretroviral therapy drugs, might be more useful in estimating CVD risks in HIV-infected persons than conventional risk prediction models.
authors.affiliation: Copenhagen HIV Programme (CHIP), University of Copenhagen/Faculty of Health Science, Copenhagen, Denmark. nfm@cphiv.dk
authors.forename: Nina
authors.initials: N
authors.lastname: Friis-Møller
authors.forename: Rodolphe
authors.initials: R
authors.lastname: Thiébaut
authors.forename: Peter
authors.initials: P
authors.lastname: Reiss
authors.forename: Rainer
authors.initials: R
authors.lastname: Weber
authors.forename: Antonella D'Arminio
authors.initials: AD
authors.lastname: Monforte
authors.forename: Stephane
authors.initials: S
authors.lastname: De Wit
authors.forename: Wafaa
authors.initials: W
authors.lastname: El-Sadr
authors.forename: Eric
authors.initials: E
authors.lastname: Fontas
authors.forename: Signe
authors.initials: S
authors.lastname: Worm
authors.forename: Ole
authors.initials: O
authors.lastname: Kirk
authors.forename: Andrew
authors.initials: A
authors.lastname: Phillips
authors.forename: Caroline A
authors.initials: CA
authors.lastname: Sabin
authors.forename: Jens D
authors.initials: JD
authors.lastname: Lundgren
authors.forename: Matthew G
authors.initials: MG
authors.lastname: Law
mesh_terms: D000328:Adult; D019380:Anti-HIV Agents / Q000009:adverse effects*; D001118:Argentina; D001315:Australia; D003327:Coronary Disease / Q000139:chemically induced* / Q000401:mortality / Q000628:therapy; D004359:Drug Therapy, Combination; D005060:Europe; D005260:Female; D015658:HIV Infections / Q000188:drug therapy* / Q000401:mortality; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000139:chemically induced* / Q000401:mortality / Q000628:therapy; D011446:Prospective Studies; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D019380:Anti-HIV Agents