Therapeutic Area
ASCVD/CVD Risk Assessment
Background
American Heart Association/American College of Cardiology primary prevention guidelines recommend estimation of 30-year cardiovascular disease (CVD) risk to guide clinician-patient discussions in younger adults. While the novel AHA PREVENT equations included 30-year risk models, interpretation of these risk estimates is challenging for both clinicians and patients. Standardized risk percentiles based on the U.S. population may provide a useful and accessible tool to optimize risk communication.
Methods
Using data from the 2011 to 2018 National Health and Nutrition Examination Surveys (NHANES) in U.S. adults aged 30-59 years, we estimated the population-level distribution of 30-year risk for CVD (which includes atherosclerotic CVD [ASCVD] and heart failure [HF]) using the AHA PREVENT equations. We calculated the 30-year risk corresponding to percentile ranks and generated age- and sex-specific standardized risk percentiles for CVD, ASCVD, and HF.
Results
Among 9,204 participants, representing approximately 109 million US adults, 34% were 30-39 years old, 31% were 40-49 years old, and 35% were 50-59 years old. The population-level distribution of 30-year risk for CVD, ASCVD, and HF was significantly higher in older age strata and in males compared with females (Figure). Among females, the 30-year absolute risk for CVD that represented the 75th percentile (i.e., only 25% of age- and sex-matched peers would have higher risk) was 6% for 30 to 39- year-olds, 16% for 40 to 49-year-olds, and 29% for 50 to 59-year-olds. Among males, the 30-year absolute risk for CVD that represented the 75th percentile was 11% for 30 to 39-year-olds, 23% for 40 to 49-year-olds, and 33% for 50 to 59-year-olds. Similar patterns were observed for percentile distributions in 30-year risk estimates for ASCVD and HF.
Conclusions
Translation of PREVENT-based 30-year CVD, ASCVD, and HF risk estimates into age- and sex-standardized percentiles may offer a useful tool for clinicians and patients to interpret risk.