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Published on: December 1, 2011
Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis
Junwen Yu1, Xiaoning Liu2,3, Zheng Zhu1,4,5
1School of Nursing, Fudan University, Shanghai, China.
Insights
Cardiovascular disease (CVD) risk models for people living with HIV (PLWH) were compared. The full D:A:D (2016) model showed the best discrimination, but no significant differences were found between models. Further research is needed for specific populations.
Area of Science:
- Cardiology
- Infectious Diseases
- Epidemiology
Background:
- Cardiovascular disease (CVD) poses a significant risk for people living with HIV (PLWH), with a 2.16 times higher relative risk compared to non-infected individuals.
- Predicting CVD risk is crucial for managing HIV, yet no consensus exists on optimal risk prediction models for PLWH.
- This study systematically reviews and compares existing CVD risk prediction models in the context of HIV management.
Purpose of the Study:
- To systematically summarize and compare the performance of prediction models for cardiovascular disease (CVD) risk among people living with HIV (PLWH).
- To identify the most effective CVD risk prediction models for individuals with HIV.
- To highlight gaps in current research regarding CVD risk prediction in specific PLWH populations.
Main Methods:
- A systematic search of longitudinal studies developing or validating CVD risk prediction models for PLWH was conducted across five databases up to January 2022.
- The Prediction model Risk Of Bias ASsessment Tool (PROBAST) was used to evaluate the quality of included studies.
- Meta-analysis was applied to pool C-statistics for assessing the discrimination performance of the models.
Main Results:
- Thirteen articles detailing 17 models were included, with all studies exhibiting a high risk of bias.
- The full D:A:D (2016) model demonstrated the best discrimination (C-statistic: 0.77), followed by D:A:D (2010) and Pooled Cohort Equations (PCE).
- No significant differences in discrimination were observed between any model pairings. The PCE showed better discrimination in individuals aged ≤40 years. No models were developed for Sub-Saharan Africa or Asia.
Conclusions:
- The full D:A:D (2016) model exhibited superior discrimination, though differences among models were not statistically significant.
- There is a need to develop specific CVD risk models for older PLWH and for those residing in Sub-Saharan Africa and Asia.
- High risk of bias was noted across included studies, emphasizing the need for higher-quality research.
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.
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