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Performance of Cardiovascular Risk Prediction Models Among People Living With HIV: A Systematic Review and
Cullen Soares1, Michael Kwok2, Kent-Andrew Boucher3
1Department of Medicine, University of Maryland School of Medicine, Baltimore.
Insights
Cardiovascular disease (CVD) risk scores, both general and HIV-specific, show moderate performance in people with HIV, often underpredicting risk. Current guidelines recommending HIV as a risk-enhancing factor remain relevant.
Area of Science:
- Medical research
- Epidemiology
- Public health
Background:
- Cardiovascular disease (CVD) is a significant concern for individuals living with HIV.
- Existing data on the effectiveness of CVD risk score models in this population are not synthesized.
- Accurate risk assessment is crucial for effective CVD prevention strategies in people with HIV.
Purpose of the Study:
- To systematically review and synthesize data on the performance of various cardiovascular disease risk score models in people living with HIV.
- To compare the predictive accuracy of general population versus HIV-specific risk scores.
- To inform clinical practice and guideline development for CVD risk assessment in people with HIV.
Main Methods:
- A comprehensive search of PubMed and Embase databases was conducted up to January 31, 2021.
- Included studies were observational cohorts of adults with HIV, assessing CVD outcomes and reporting at least one CVD risk score.
- Data on study characteristics, CVD outcomes, and risk models were extracted, with measures of calibration and discrimination summarized and meta-analyzed where possible.
Main Results:
- Nine studies involving over 75,000 individuals with HIV were analyzed, evaluating ten different risk prediction scores.
- Most risk scores demonstrated moderate discrimination (C-statistic 0.7-0.8), with no significant difference between general and HIV-specific models.
- Models generally underpredicted CVD risk, though Framingham Risk Score and Pooled Cohort Equations showed better calibration.
Conclusions:
- Both general and HIV-specific CVD risk models exhibit comparable, moderate predictive ability in people living with HIV.
- A consistent tendency for underprediction of CVD risk was observed across most models.
- Findings support current guidelines that advocate for considering HIV as a risk-enhancing factor in CVD risk estimation.
Importance:
Extant data on the performance of cardiovascular disease (CVD) risk score models in people living with HIV have not been synthesized.
Objective:
To synthesize available data on the performance of the various CVD risk scores in people living with HIV.
Data Sources:
PubMed and Embase were searched from inception through January 31, 2021.
Study Selection:
Selected studies (1) were chosen based on cohort design, (2) included adults with a diagnosis of HIV, (3) assessed CVD outcomes, and (4) had available data on a minimum of 1 CVD risk score.
Data Extraction And Synthesis:
Relevant data related to study characteristics, CVD outcome, and risk prediction models were extracted in duplicate. Measures of calibration and discrimination are presented in tables and qualitatively summarized. Additionally, where possible, estimates of discrimination and calibration measures were combined and stratified by type of risk model.
Main Outcomes And Measures:
Measures of calibration and discrimination.
Results:
Nine unique observational studies involving 75 304 people (weighted average age, 42 years; 59 490 male individuals [79%]) living with HIV were included. In the studies reporting these data, 86% were receiving antiretroviral therapy and had a weighted average CD4+ count of 449 cells/μL. Included in the study were current smokers (50%), patients with diabetes (5%), and patients with hypertension (25%). Ten risk prediction scores (6 in the general population and 4 in the HIV-specific population) were analyzed. Most risk scores had a moderate performance in discrimination (C statistic: 0.7-0.8), without a significant difference in performance between the risk scores of the general and HIV-specific populations. One of the HIV-specific risk models (Data Collection on Adverse Effects of Anti-HIV Drugs Cohort 2016) and 2 of the general population risk models (Framingham Risk Score [FRS] and Pooled Cohort Equation [PCE] 10 year) had the highest performance in discrimination. In general, models tended to underpredict CVD risk, except for FRS and PCE 10-year scores, which were better calibrated. There was substantial heterogeneity across the studies, with only a few studies contributing data for each risk score.
Conclusions And Relevance:
Results of this systematic review and meta-analysis suggest that general population and HIV-specific CVD risk models had comparable, moderate discrimination ability in people living with HIV, with a general tendency to underpredict risk. These results reinforce the current recommendations provided by the American College of Cardiology/American Heart Association guidelines to consider HIV as a risk-enhancing factor when estimating CVD risk.
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