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Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis
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 o...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077152/ https://www.ncbi.nlm.nih.gov/pubmed/37034346 http://dx.doi.org/10.3389/fcvm.2023.1138234 |
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author | Yu, Junwen Liu, Xiaoning Zhu, Zheng Yang, Zhongfang He, Jiamin Zhang, Lin Lu, Hongzhou |
author_facet | Yu, Junwen Liu, Xiaoning Zhu, Zheng Yang, Zhongfang He, Jiamin Zhang, Lin Lu, Hongzhou |
author_sort | Yu, Junwen |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10077152 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100771522023-04-07 Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis Yu, Junwen Liu, Xiaoning Zhu, Zheng Yang, Zhongfang He, Jiamin Zhang, Lin Lu, Hongzhou Front Cardiovasc Med Cardiovascular Medicine 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. Frontiers Media S.A. 2023-03-23 /pmc/articles/PMC10077152/ /pubmed/37034346 http://dx.doi.org/10.3389/fcvm.2023.1138234 Text en © 2023 Yu, Liu, Zhu, Yang, He, Zhang and Lu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Yu, Junwen Liu, Xiaoning Zhu, Zheng Yang, Zhongfang He, Jiamin Zhang, Lin Lu, Hongzhou Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis |
title | Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis |
title_full | Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis |
title_fullStr | Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis |
title_full_unstemmed | Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis |
title_short | Prediction models for cardiovascular disease risk among people living with HIV: A systematic review and meta-analysis |
title_sort | prediction models for cardiovascular disease risk among people living with hiv: a systematic review and meta-analysis |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077152/ https://www.ncbi.nlm.nih.gov/pubmed/37034346 http://dx.doi.org/10.3389/fcvm.2023.1138234 |
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