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Comparative performance of cardiovascular risk prediction models in people living with HIV
Irtiza S Tahir1, Alinda G Vos1,2, Johanna A A Damen3
1Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands.
Insights
Cardiovascular risk models show low predicted risk in people with HIV in South Africa. Framingham models aligned with D:A:D 2010, but other models underestimated high-risk individuals, highlighting the need for tailored risk assessment tools.
Area of Science:
- Public Health
- Infectious Diseases
- Cardiology
Background:
- General cardiovascular disease (CVD) risk assessment tools are used for people living with HIV (PLWH).
- The applicability of these general tools in sub-Saharan African (SSA) populations remains uncertain.
- Accurate CVD risk stratification is crucial for effective management in PLWH in SSA.
Purpose of the Study:
- To compare the performance of common CVD risk prediction models against the D:A:D (Data Collection on Adverse Events of Anti-HIV Drugs) 2010 and 2016 models.
- To assess cardiovascular risk classification in people living with HIV in rural South Africa.
- To evaluate the agreement between different CVD risk models in this specific population.
Main Methods:
- Utilized data from the Ndlovu Cohort Study in rural South Africa, including 735 HIV-infected individuals.
- Estimated CVD risk using Framingham Cardiovascular and Heart Disease (FHS-CVD, FHS-CHD), Atherosclerotic Cardiovascular Disease (ASCVD), and D:A:D 2010/2016 models.
- Classified participants into low, moderate, or high CVD risk categories and used Kappa statistics to assess model agreement.
Main Results:
- The majority of participants (n=735) were women (56.7%) with a mean age of 43.9 years.
- Median predicted CVD risk was generally low across models (3-5%), with high 10-year CVD risk predicted for 0.5% to 6.6% of participants.
- Kappa statistics indicated moderate agreement between models, with FHS-CVD showing the highest agreement (0.60) compared to D:A:D 2010.
Conclusions:
- Overall predicted CVD risk appears low in this South African HIV-infected cohort.
- Framingham Cardiovascular and Heart Disease (FHS-CVD) model showed similar risk classification to the D:A:D 2010 model.
- Most models, except D:A:D, underestimated high CVD risk, emphasizing the need for prospective studies to develop validated CVD risk algorithms for SSA PLWH.
Background:
Current cardiovascular risk assessment in people living with HIV is based on general risk assessment tools; however, whether these tools can be applied in sub-Saharan African populations has been questioned.
Objectives:
The study aimed to assess cardiovascular risk classification of common cardiovascular disease (CVD) risk prediction models compared to the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) 2010 and 2016 models in people living with HIV.
Method:
Cardiovascular disease risk was estimated by Framingham Cardiovascular and Heart Disease (FHS-CVD, FHS-CHD), Atherosclerotic Cardiovascular Disease (ASCVD) and D:A:D 2010 and 2016 risk prediction models for HIV-infected participants of the Ndlovu Cohort Study, Limpopo, rural South Africa. Participants were classified to be at low (< 10%), moderate (10% - 20%), or high-risk (> 20%) of CVD within 10 years for general CVD and five years for D:A:D models. Kappa statistics were used to determine agreement between CVD risk prediction models. Subgroup analysis was performed according to age.
Results:
The analysis comprised 735 HIV-infected individuals, predominantly women (56.7%), average age 43.9 (8.8) years. The median predicted CVD risk for D:A:D 2010 and FHS-CVD was 4% and for ASCVD and FHS-CHD models, 3%. For the D:A:D 2016 risk prediction model, the figure was 5%. High 10-year CVD risk was predicted for 2.9%, 0.5%, 0.7%, 3.1% and 6.6% of the study participants by FHS-CVD, FHS-CHD, ASCVD, and D:A:D 2010 and 2016. Kappa statistics ranged from 0.34 for ASCVD to 0.60 for FHS-CVD as compared to the D:A:D 2010 risk prediction model.
Conclusion:
Overall, predicted CVD risk is low in this population. Compared to D:A:D 2010, CVD risk estimated by the FHS-CVD model showed similar overall results for risk classification. With the exception of the D:A:D model, all other risk prediction models classified fewer people to be at high estimated CVD risk. Prospective studies are needed to develop and validate CVD risk algorithms in people living with HIV in sub-Saharan Africa.
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