Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis
- PMID: 37034346
- PMCID: PMC10077152
- DOI: 10.3389/fcvm.2023.1138234
Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis
Abstract
Background: HIV continues to be a major global health issue. The relative risk of cardiovascular disease (CVD) among people living with HIV (PLWH) was 2.16 compared to non-HIV-infections. The prediction of CVD is becoming an important issue in current HIV management. However, there is no consensus on optional CVD risk models for PLWH. Therefore, we aimed to systematically summarize and compare prediction models for CVD risk among PLWH.
Methods: Longitudinal studies that developed or validated prediction models for CVD risk among PLWH were systematically searched. Five databases were searched up to January 2022. The quality of the included articles was evaluated by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). We applied meta-analysis to pool the logit-transformed C-statistics for discrimination performance.
Results: Thirteen articles describing 17 models were included. All the included studies had a high risk of bias. In the meta-analysis, the pooled estimated C-statistic was 0.76 (95% CI: 0.72-0.81, I 2 = 84.8%) for the Data collection on Adverse Effects of Anti-HIV Drugs Study risk equation (D:A:D) (2010), 0.75 (95% CI: 0.70-0.79, I 2 = 82.4%) for the D:A:D (2010) 10-year risk version, 0.77 (95% CI: 0.74-0.80, I 2 = 82.2%) for the full D:A:D (2016) model, 0.74 (95% CI: 0.68-0.79, I 2 = 86.2%) for the reduced D:A:D (2016) model, 0.71 (95% CI: 0.61-0.79, I 2 = 87.9%) for the Framingham Risk Score (FRS) for coronary heart disease (CHD) (1998), 0.74 (95% CI: 0.70-0.78, I 2 = 87.8%) for the FRS CVD model (2008), 0.72 (95% CI: 0.67-0.76, I 2 = 75.0%) for the pooled cohort equations of the American Heart Society/ American score (PCE), and 0.67 (95% CI: 0.56-0.77, I 2 = 51.3%) for the Systematic COronary Risk Evaluation (SCORE). In the subgroup analysis, the discrimination of PCE was significantly better in the group aged ≤40 years than in the group aged 40-45 years (P = 0.024) and the group aged ≥45 years (P = 0.010). No models were developed or validated in Sub-Saharan Africa and the Asia region.
Conclusions: The full D:A:D (2016) model performed the best in terms of discrimination, followed by the D:A:D (2010) and PCE. However, there were no significant differences between any of the model pairings. Specific CVD risk models for older PLWH and for PLWH in Sub-Saharan Africa and the Asia region should be established.Systematic Review Registration: PROSPERO CRD42022322024.
Keywords: AIDS; HIV; cardiovascular disease; meta-analysis; prediction model; systematic review.
© 2023 Yu, Liu, Zhu, Yang, He, Zhang and Lu.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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References
-
- World Health Organization. Data on the size of the HIV/AIDS epidemic. Available at: https://www.who.int/data/gho/data/themes/topics/topic-details/GHO/data-o... (Accessed March 30, 2022).
-
- World Health Organization. Cardiovascular diseases (CVDs). Available at: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases...) (Accessed March 30, 2022).
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