3.9 Article

Predicting the risk of cardiovascular disease in HIV-infected patients: the Data collection on Adverse Effects of Anti-HIV Drugs Study

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1097/HJR.0b013e328336a150

关键词

antiretroviral drugs; cardiovascular risk; HIV; prediction model

资金

  1. Oversight Committee for The Evaluation of Metabolic Complications of HAART
  2. Health Insurance Fund Council, Amstelveen, The Netherlands [CURE/97-46486]
  3. Agence Nationale de Recherches sur le SIDA
  4. Australian Government Department of Health and Ageing
  5. U.S. National Institutes of Health's National Institute of Allergey and Infectious Diseases (NIAID) [U01-AI069907]
  6. Foundation for AIDS Research
  7. Fondo de Investigacion Sanitaria (FIS) [99/0887]
  8. Fundacion para la Investigacion y la Prevencion del SIDA en Espana (FIPSE) [3171/00]
  9. National Institute of Allergy and Infectious Diseases, National Institutes of Health [5U01AI042170-10, 5U01AI046362-03]
  10. BIOMED 1 [CT94-1637]
  11. BIOMED 2 [CT97-2713]
  12. European Commission [QLK2-2000-00773]
  13. Bristol-Myers Squibb
  14. GlaxoSmithKline
  15. Boehringer Ingelheim
  16. Roche
  17. Abbott
  18. Gilead
  19. GSK
  20. Pfizer
  21. Janssen-Cilag
  22. Swiss National Science Foundation

向作者/读者索取更多资源

Aims 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. Methods and 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. Conclusion 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. Eur J Cardiovasc Prev Rehabil 17:491-501 (C) 2010 The European Society of Cardiology

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