Key result
The CARPA-adjusted FHS CVD risk equation combined with clinical criteria performed best, scoring 64% of those who had CVD events as high risk, whereas most equations underestimated risk by 14% to 55%.
Why the study?
The performance of cardiovascular disease risk prediction equations in Indigenous Australians was not well established.
Which cardiovascular risk prediction equation performs best in Indigenous Australians?
Meta-Analysis (n=3,618)
Yes
Which cardiovascular risk prediction equation performs best in Indigenous Australians?
The CARPA-adjusted Framingham Heart Study equation combined with clinical criteria provides the best cardiovascular risk prediction for Indigenous Australians, though further refinement is needed.
Supports CARPA-adjusted FHS equation plus clinical criteria in Indigenous Australians; extends validation data while leaving open need for prospective refinement.
OBJECTIVE: To assess the performance of cardiovascular disease (CVD) risk equations in Indigenous Australians. METHODS: We conducted an individual participant meta-analysis using longitudinal data of 3618 Indigenous Australians (55% women) aged 30-74 years without CVD from population-based cohorts of the Cardiovascular Risk in IndigenouS People(CRISP) consortium. Predicted risk was calculated using: 1991 and 2008 Framingham Heart Study (FHS), the Pooled Cohorts (PC), GloboRisk and the Central Australian Rural Practitioners Association (CARPA) modification of the FHS equation. Calibration, discrimination and diagnostic accuracy were evaluated. Risks were calculated with and without the use of clinical criteria to identify high-risk individuals. RESULTS: When applied without clinical criteria, all equations, except the CARPA-adjusted FHS, underestimated CVD risk (range of percentage difference between observed and predicted CVD risks: -55% to -14%), with underestimation greater in women (-63% to -13%) than men (-47% to -18%) and in younger age groups. Discrimination ranged from 0.66 to 0.72. The CARPA-adjusted FHS equation showed good calibration but overestimated risk in younger people, those without diabetes and those not at high clinical risk. When clinical criteria were used with risk equations, the CARPA-adjusted FHS algorithm scored 64% of those who had CVD events as high risk; corresponding figures for the 1991-FHS were 58% and were 87% for the PC equation for non-Hispanic whites. However, specificity fell. CONCLUSION: The CARPA-adjusted FHS CVD risk equation and clinical criteria performed the best, achieving higher combined sensitivity and specificity than other equations. However, future research should investigate whether modifications to this algorithm combination might lead to improved risk prediction.
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Barr et al. (2020) conducted a meta-analysis in Cardiovascular disease risk (n=3,618). Cardiovascular disease risk prediction equations (e.g., CARPA-adjusted FHS) vs. Observed CVD events was evaluated on Calibration, discrimination and diagnostic accuracy of CVD risk equations. The CARPA-adjusted FHS CVD risk equation combined with clinical criteria performed best, scoring 64% of those who had CVD events as high risk, whereas most equations underestimated risk by 14% to 55%.
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