Population-based age- and sex-specific percentiles showing 30-year absolute risk estimates for cardiovascular disease, atherosclerotic cardiovascular disease (ASCVD) and heart failure (HF) based on PREVENT equations may offer an opportunity to improve risk perception and shared decision-making among younger adults, ultimately motivating healthy behavior changes, increasing medication adherence and potentially improving outcomes, according to a recent study published in JACC.
PREVENT, which estimates the 10-year and 30-year risk for total cardiovascular disease, was developed in 2023 and differs from previous equations in that it combines cardiovascular, kidney, and metabolic health measures to assess risk. New guidelines, including the ACC/AHA High Blood Pressure Guideline, use PREVENT equations in place of previously used pooled cohort equations to estimate risk and guide drug treatment.
In this study, Vaishnavi Krishnan, BS; Xiaoning Huang, PhD, et al., used data from approximately 8,700 U.S. adults between the ages of 30 and 59 years without prevalent cardiovascular disease who were enrolled in the National Health and Nutrition Examination Survey (NHANES) to calculate 30-year risk using the PREVENT equations and then derive age- and sex-specific percentiles for cardiovascular disease, ASCVD and HF.
Overall findings showed the median absolute cardiovascular disease risk to be 13%. Broken down by corresponding age- and sex-specific percentiles, absolute risk estimates for cardiovascular disease, ASCVD and HF were higher among both men and women who were older vs. younger. For example, in a 35-year-old woman, the 75th percentile of 30-year cardiovascular disease risk was 5.6% compared with 14.7% at 45 years and 25.6% at 55 years. Similarly, for a 35-year-old man, the 75th percentile of 30-year cardiovascular disease risk was 10.4% compared with 21.2% at 45 and 31.4% at 55.
Krishnan, et al., also noted a greater prevalence of cardiovascular disease risk factors, including diabetes and hypertension, among those individuals at higher percentiles of overall 30-year risk. Diabetes, for example, was significantly higher among both men and women in the 75th percentile of risk or above compared with those in the lowest 25th percentile. Additionally, treatment for risk factors was much higher among those in the upper percentiles vs. lower percentiles. For example, approximately 38% of women in the 75th percentile were taking antihypertensives compared with less than 1% of those in the 25th percentile.
“These percentiles – when used with absolute 30-year risk – may enhance risk communication and support shared decision-making between clinicians and patients by providing a comparison to age- and sex-matched peers for 30-year cardiovascular disease risk estimates,” write Krishnan and colleagues.
In a related editorial comment, Erica S. Spatz, MD, MHS, FACC, said the findings hold potential for addressing the cognitive biases and perceptions tied to susceptibility, benefits and barriers that inform health beliefs in younger adults. She stresses the importance of “peer comparison, reduction of structural barriers, integration of metrics and feedback on progress, and shifting framing to more positive agency around healthy aging,” but also highlights the need for “iterative testing with patient and clinician feedback.”
Meanwhile, two other studies also published in JACC continue to evaluate the use of PREVENT equations in adequately determining patient risk.
In one study, Hokyou Lee, MD, PhD, et al., analyzed how well PREVENT equations performed in a non-US sample of 7.7 million Korean adults and found they demonstrated “good discriminations” for total cardiovascular disease and its subtypes, as well as “good calibration” for cardiovascular disease and ASCVD. “This is noteworthy because prior U.S.-based models generally overestimated risk in East Asian populations,” said Lee. “Understanding the global transportability of PREVENT will help us speak the same ‘risk language’ in multinational trials and observational studies that need a consistent risk framework.”
“This study adds to the growing body of evidence on the performance of the PREVENT model across diverse populations,” said Eugene Yang, MD, MS, FACC, a co-author on the study and past chair of ACC’s Prevention of Cardiovascular Disease Member Section. “It was encouraging to see strong overall performance in a homogeneous Korean cohort, though the model overestimated HF risk in men. These findings highlight opportunities to refine the model by incorporating additional variables such as HbA1c and urine albumin-to-creatinine ratio.”
In a second study, Isaac Acquah, MD, MPH, et al., examined the prognostic value of coronary artery calcium (CAC) for risk stratification when using the new PREVENT equations. According to Acquah and colleagues, their overall findings “suggest that although PREVENT may outperform prior scores such as the pooled cohort equations in terms of discrimination and calibration, it may still misclassify individual risk.” They caution that even with improved risk estimation, there is still value in CAC testing in identifying asymptomatic individuals with substantial risk who are likely to benefit from preventive interventions. “Consistent with previous guidelines, we support a tailored approach to risk stratification, where PREVENT is used for initial screening and CAC is considered when risk is uncertain,” they write.
Krishnan, V, Huang, X, Zhang, S. et al. Age and Sex-Specific Percentiles of 30-Year Cardiovascular Disease Risk Based on the PREVENT Equations. JACC. 2025 Nov, 86 (21) 2017–2027. https://doi.org/10.1016/j.jacc.2025.09.1509
Lee, H, Inoue, K, Son, D. et al. Evaluation of the PREVENT Equations in a Nationwide Cohort of 7.7 Million Korean Adults. JACC. 2025 Dec, 86 (23) 2395–2398. https://doi.org/10.1016/j.jacc.2025.09.1591
Acquah, I, Hagan, K, Shapiro, M. et al. Interplay of Coronary Artery Calcium and PREVENT Equations in Atherosclerotic Cardiovascular Disease Risk Prediction. JACC. 2025. https://doi.org/10.1016/j.jacc.2025.09.1576