Key result
PREVENT-CVD accurately predicts 10-year total CVD risk with a ~0.79 C-statistic.
Why the study?
The American Heart Association PREVENT equations needed external validation in large contemporary samples across multiple health systems in the United States.
Cohort (n=680,864)
Yes
The PREVENT equations demonstrated accurate discrimination and calibration for predicting 10-year risk of CVD, ASCVD, and HF in a large national sample of US adults, supporting their use in clinical practice.
Answers are grounded in this paper and cite their sources.
Captured external expert commentary on this paper, strongest first. Original sources are linked where available.
“Risk equations are useful only insofar as they estimate risk accurately in the settings in which treatment decisions are made. Their real test is calibration in contemporary, heterogeneous populations, particularly when estimates are used to initiate therapies, communicate prognosis, and allocate preventive resources. The American Heart Association Predicting Risk of Cardiovascular Disease Events (PREVENT) equations were designed for this changing landscape.”
“Overall, the study by Khan et al strengthens confidence that PREVENT can reliably support contemporary risk-based prevention across total CVD, ASCVD, and HF. The next challenge is to translate validated prediction into equitable action across the CKM continuum, while continuing to test, recalibrate, and improve the equations in the populations and care settings for whom prevention matters most.”
“The separate PREVENT outcomes may also help clinicians identify whether an individual's dominant predicted burden is ASCVD, HF, or both, allowing prevention discussions to better reflect the full spectrum of CKM risk. The findings also add to an expanding body of external-validation evidence.”
Supports PREVENT use for contemporary US risk estimation; extends validation to large EHR cohorts but leaves adoption open pending trials.
BACKGROUND: The American Heart Association Predicting Risk of Cardiovascular Disease EVENT (PREVENT) equations were developed from observational research cohorts and electronic health record data and provide sex-specific risk estimates for cardiovascular disease (CVD), atherosclerotic CVD (ASCVD), and heart failure (HF). External validation in large contemporary samples across multiple health systems in the United States is needed. METHODS: We assembled a national electronic health record-based cohort of US adults with individual-level patient data pooled from a collective of 30 health systems (Truveta) to externally validate the outcome-specific 10-year PREVENT equations (PREVENT-CVD, PREVENT-ASCVD, and PREVENT-HF). We included patients aged 30 to 79 years without a history of prior CVD and with an ambulatory encounter in the electronic health record between 2013 and 2018. The outcomes were defined as total CVD (composite of ASCVD and HF), ASCVD, and HF through December 2024 using diagnosis codes. Model performance of the outcome-specific PREVENT base equations was assessed with the Harrell C statistic and calibration slope, stratified by sex. RESULTS: Of the 680 864 adults included, the mean (SD) age was 55 (13) years, and 56% were female. Over a mean (SD) follow-up of 6.8 (2.3) years, there were 29 535 incident CVD events, 19 280 incident ASCVD events, and 16 824 incident HF events. The median (interquartile range) 10-year predicted risk of PREVENT-CVD among women was 3.6% (1.3%-8.8%), and among men was 5.8% (2.5%-11.7%). The C statistic (95% CI) was 0.788 (0.786-0.790), and the calibration slope (95% CI) was 0.98 (0.95-1.01) for PREVENT-CVD. PREVENT-ASCVD and PREVENT-HF demonstrated similar C statistics (0.774 [0.771-0.777] and 0.824 [0.820-0.828]) and calibration slopes (1.07 [1.04-1.10] and 1.01 [0.97-1.04]) for prediction of the 10-year risk of ASCVD and HF, respectively. CONCLUSIONS: The PREVENT equations accurately and precisely estimate the 10-year risk of CVD, ASCVD, and HF in a large sample of US adults. These findings support the generalizability of the PREVENT equations to inform guideline-recommended risk assessment and preventive efforts.
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Khan et al. (2026) conducted a cohort in Cardiovascular disease risk (n=680,864). PREVENT equations was evaluated on total CVD (composite of ASCVD and HF) (C statistic 0.788, 95% CI 0.786-0.790). The PREVENT-CVD equation accurately predicted 10-year cardiovascular disease risk in US adults, demonstrating a C statistic of 0.788 (95% CI 0.786-0.790).
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