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Eur J Prev Cardiol. 2016 Jan;23(2):214-23. doi: 10.1177/2047487315579291. Epub 2015 Apr 16.

An updated prediction model of the global risk of cardiovascular disease in HIV-positive persons: The Data-collection on Adverse Effects of Anti-HIV Drugs (D:A:D) study.

Author information

1
Odense University Hospital, Department of Infectious Diseases, Denmark nina.friis-moeller@rsyd.dk.
2
Copenhagen HIV Programme, Department of Infectious Diseases and Rheumatology, University of Copenhagen, Denmark.
3
Research Department of Infection and Population Health, UCL, London, UK.
4
Division of Infectious Diseases, University Hospital Zurich, University of Zurich, Switzerland.
5
Academic Medical Centre, University of Amsterdam, and Stichting HIV Monitoring, The Netherlands.
6
University of Bordeaux, ISPED, France.
7
Department of Infectious Diseases, Centre Hospitalier Universitaire St Pierre Hospital, Brussels, Belgium.
8
Department of Infectious Diseases, Hospital San Paolo, University of Milan, Italy.
9
Department de Santé Publique, Centre Hospitalier Universitaire de Nice, France.
10
The Kirby Institute, University of New South Wales, Sydney, Australia.

Abstract

BACKGROUND:

With the aging of the population living with HIV, the absolute risk of cardiovascular disease (CVD) is increasing. There is a need to further facilitate the identification of persons at elevated risk in routine practice.

METHODS AND RESULTS:

Prospective information was collected on 32,663 HIV-positive persons 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 (D:A:D) study. Cox regression models (full and reduced) were developed that predict the risk of a global CVD endpoint. The predictive performance of the D:A:D models were compared with a recent CVD prediction model from the Framingham study, which was assessed recalibrated to the D:A:D dataset. A total of 1010 CVD events occurred during 186,364.5 person-years. The full D:A:D CVD prediction model included age, gender, systolic blood pressure, smoking status, family history of CVD, diabetes, total cholesterol, high-density lipoprotein, CD4 lymphocyte count, cumulative exposure to protease- and nucleoside reverse transcriptase-inhibitors, and current use of abacavir. A reduced model omitted antiretroviral therapies. The D:A:D models statistically significantly predicted risk more accurately than the recalibrated Framingham model (Harrell's c-statistic of 0.791, 0.783 and 0.766 for the D:A:D full, D:A:D reduced, and Framingham models respectively; p < 0.001). The D:A:D models also more accurately predicted five-year CVD-risk for key prognostic subgroups.

CONCLUSIONS:

An updated, easily recalibrated, global CVD-risk equation tailored to HIV-positive persons was developed using routinely collected CVD risk parameters and incorporating markers on immune function (CD4 lymphocyte count), and exposure to antiretroviral therapies. The estimated CVD risk can be used to quantify risk and to guide preventive care.

KEYWORDS:

AIDS; CVD risk prediction; HIV; epidemiology

PMID:
25882821
DOI:
10.1177/2047487315579291
[Indexed for MEDLINE]

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