Performance of Cardiovascular Risk Prediction Models Among People Living With HIV: A Systematic Review and Meta-analysis

Abstract

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.

Figure 1.. Pooled Analysis of Discrimination Measures (Area Under Operator Curves) Reported by Individual Studies for 4 Cardiovascular Disease (CVD) Risk Prediction Models

Black boxes represent the C statistic (C index) estimates and the horizontal bars represent the 95% CIs. The size of the boxes is proportional to the inverse variance. The blue diamonds are for the pooled relative risk estimate and 95% CIs using random-effects models. Thompson-Paul et al, 2016, did not report SE or CI for the C statistic estimates; therefore, the SE for the C statistic estimate for each risk model was imputed from studies with similar number of cases, ie, Friis-Møller et al, 2010 (Framingham Risk Score [FHS] 10 year, Pooled Cohort Equation [PCE] 10 year, 2010 Data Collection on Adverse Effects of Anti-HIV Drugs Cohort [D:A:D] 5 year), De Socio et al 2017 (Systematic Coronary Risk Evaluation [SCORE]), and Triant et al, 2018 (PCE 5 year).

Figure 2.. Synthesis of Calibration Measures (Observed to Expected [O:E] Ratios) for 5 Risk-Prediction Models Reported in 9 Studies Included in the Present Meta-analysis

Calibration data for risk models only assessed in a single study (ie, The Cuore Project [CUORE], Copenhagen, Framingham-Registre Gironí del COR [REGICORE], HIV Myocardial Infarction [HIVMI1], Veterans Aging Cohort Study [VACS] Index) are not shown in this Figure. For D:A:D 2010 and D:A:D 2016 cardiovascular disease (CVD) risk models, only the 5-year full model calibration data are shown in the Figure (Table 2 contains calibration data on D:A:D 2010 and D:A:D 2016 10 year and D:A:D 2016–limited models). For calibration measures of the Framingham Risk Score (FRS) model in the D:A:D study, only 2016 data are shown in the Figure to avoid presenting overlapping data with the D:A:D 2010 report. Tables 2 and 3 contain data on calibration measures not presented in this Figure. PCE indicates Pooled Cohort Equation.