Cardiovascular risk prediction in HIV‐infected patients: comparing the Framingham, atherosclerotic cardiovascular disease risk score (ASCVD), Systematic Coronary Risk Evaluation for the Netherlands (SCORE‐NL) and Data Collection on Adverse Events of Anti‐HIV Drugs (D:A:D) risk prediction models. Issue 4 (12th August 2015)

• Record Type: Journal Article
• Authors: Krikke, M; Hoogeveen, RC; Hoepelman, AIM; Visseren, FLJ; Arends, JE
• Is Part Of: HIV medicine. Volume 17:Issue 4(2016:Apr.)
• Page Start: 289
• Page End: 297
• Publication Date: 2015-08-12
• Subjects: atherosclerotic cardiovascular disease risk score (ASCVD) -- cardiovascular disease -- data collection on adverse events of anti‐HIV drugs (D:A:D) -- framingham -- HIV infection -- risk prediction -- systematic coronary risk evaluation (SCORE); HIV infections -- Treatment -- Periodicals; HIV-positive persons -- Periodicals; HIV infections -- Treatment -- Decision making -- Periodicals; 616.9792
• DOI: 10.1111/hiv.12300
• Languages: English
• ISSNs: 1464-2662

Abstract

Abstract : Objectives: The aim of the study was to compare the predictions of five popular cardiovascular disease (CVD) risk prediction models, namely the Data Collection on Adverse Events of Anti‐HIV Drugs (D:A:D) model, the Framingham Heart Study (FHS) coronary heart disease (FHS‐CHD) and general CVD (FHS‐CVD) models, the American Heart Association (AHA) atherosclerotic cardiovascular disease risk score (ASCVD) model and the Systematic Coronary Risk Evaluation for the Netherlands (SCORE‐NL) model. Methods: A cross‐sectional design was used to compare the cumulative CVD risk predictions of the models. Furthermore, the predictions of the general CVD models were compared with those of the HIV‐specific D:A:D model using three categories (< 10%, 10–20% and > 20%) to categorize the risk and to determine the degree to which patients were categorized similarly or in a higher/lower category. Results: A total of 997 HIV‐infected patients were included in the study: 81% were male and they had a median age of 46 [interquartile range (IQR) 40–52] years, a known duration of HIV infection of 6.8 (IQR 3.7–10.9) years, and a median time on ART of 6.4 (IQR 3.0–11.5) years. The D:A:D, ASCVD and SCORE‐NL models gave a lower cumulative CVD risk, compared with that of the FHS‐CVD and FHS‐CHD models. Comparing the general CVD models with the D:A:D model, the FHS‐CVD and FHS‐CHD models only classified 65% and 79% of patients, respectively, in the same category as did the D:A:D model. However, for the ASCVD and SCORE‐NL models, this percentage was 89% and 87%, respectively. Furthermore, FHS‐CVD and FHS‐CHD attributed a higher CVD risk to 33% and 16% of patients, respectively, while this percentage was < 6% for ASCVD and SCORE‐NL. Conclusions: When using FHS‐CVD and FHS‐CHD, a higher overall CVD risk was attributed to the HIV‐infected patients than when using the D:A:D, ASCVD and SCORE‐NL models. This could have consequences regarding overtreatment, drug‐related adverse events and drug−drug interactions.