Development and Validation of AHA’s PREVENT Equations

Quick Takes

  • The new AHA’s PREVENT equations for primary prevention uses routinely available clinical variables including obesity, diabetes, kidney disease, and social risk for predicting 10- and 30-year absolute risk of CVD, each of the atherosclerotic CVDs, and HF in US adults 30-79 years of age.
  • In contrast, the ACC/AHA pooled cohort equation (PCE) for primary prevention predicts 10-year risk of CVD (coronary death, nonfatal MI, fatal or nonfatal stroke) for persons 40-79 years of age using risk strata to provide national guidelines for use of aspirin, statins, and treatment of hypertension.
  • PREVENT provides the option of adding obesity, diabetes, HbA1c, and renal function to provide data on higher-risk groups. The ACC/AHA PCE uses risk enhancers, and does not include prediction of HF.

Study Questions:

What is the value of the new American Heart Association’s (AHA’s) PREVENT equation(s) for primary prevention that use routinely available clinical variables including obesity, diabetes, kidney disease, and social risk for predicting 10- and 30-year absolute risk of cardiovascular disease (CVD) including each atherosclerotic CVD (ASCVD) and heart failure (HF) in US adults 30-79 years of age?


The PREVENT development derivation sample included individual-level participant data from 25 data sets (n = 3,281,919) between 1992 and 2017. The primary outcomes are risk of CVD, risk of each ASCVD, and risk of HF. Predictors included traditional risk factors: smoking status, systolic blood pressure (SBP), cholesterol and high-density lipoprotein cholesterol (HDL-C) with use of non–HDL-C, antihypertensive or statin use, and diabetes and estimated glomerular filtration rate.

Models were sex-specific, race-free, and adjusted for competing risk of non-CVD death. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (ASCVD and HF) and optional predictors (urine albumin-to-creatinine ratio and glycated hemoglobin [HbA1c]), and social deprivation index (SDI) were developed. SDI was calculated at the zip-code level. External validation was performed in 3,330,085 participants from 21 additional data sets. Derivation data included general population research cohorts and real-world contemporary clinical data from administrative claims and electronic medical records. Validation samples included REGARDS study which focused on stroke outcomes, CRIC which focused on renal impairment and diabetes, and older adults in the California-based Rancho Bernardo Study.


Among 6,612,004 adults, mean ± standard deviation (SD) age was 53 ± 12 years, and 56% were women. Over a mean ± SD follow-up of 4.8 ± 3.1 years, there were 211,515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763–0.809) in female and 0.757 (0.727–0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81–1.16) and 0.94 (0.81–1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration occurred in ASCVD and HF-specific models.

The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, HbA1c, and SDI were added together to the base model to total CVD (∆ C-statistic [interquartile interval] 0.004 [0.004–0.005] and 0.005 [0.004–0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84–1.20] vs. 1.39 [1.14–1.65]; p = 0.01).


AHA PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.


AHA PREVENT equations assume the physician will use the American College of Cardiology (ACC)/AHA classification of low, borderline, intermediate, and high risk and provides novel risk factors (markers). Including longitudinal research cohorts with modern real-world clinical data improves the opportunity for enhancing predictive accuracy for each type of ASCVD and HF, and the option of adding obesity, diabetes, HbA1c, and renal function provides data on higher-risk groups compared to the ACC/AHA pooled cohort equation (PCE), which also does not include HF. And PREVENT begins at 30 years, thus including young people at risk because of hypertension, obesity, and dyslipidemia, which are often linked to family history. Finally, PREVENT has a much better calibration than PCE. The slope of observed to predicted risk was close to 1 for PREVENT and ranged from 0.50 to 0.54 for PCE for ASCVD, which equates to an overestimation of risk by about 50%.

However, correlations between predicted 10-year risk of ASCVD estimated for the new base model and the PCEs were high. Based on a PCE risk estimate of 7.5%, the median PREVENT risk estimate was 8.4 (7.7–9.0) and 5.9 (5.7–6.3) for total CVD and 4.9 (4.4–5.3) and 3.7 (3.6–4.0) for ASCVD among female and male participants, respectively.

While the use of zip-codes for place-based social disadvantage in the absence of data on social determinants, it does not reflect the importance of hypertension in Black and Latino individuals, which may lead to an undertreatment bias. A 20 mm Hg higher SBP and 10 mm Hg higher diastolic BP have been associated with a doubling in the risk of death from stroke, heart disease, or other vascular disease.

Rather than relying on the original PCE risk assessment, the ACC/AHA 2018 guidelines recommend statins in groups who may have only one risk factor: those 20-75 years old and low-density lipoprotein cholesterol ≥190 mg/dL and type 2 diabetes mellitus and age 40-75 years. ACC/AHA also suggests use of risk enhancers for those at borderline or intermediate risk such as smoking, metabolic syndrome, chronic kidney disease, pre-eclampsia, premature menopause, family history of premature ASCVD, high-sensitivity C-reactive protein, coronary calcium score, lupus/rheumatoid arthritis, and psoriasis.

At this point, I feel comfortable with the PCE with risk enhancers, look forward to review by the ACC and others, and will likely try both for a while.

Clinical Topics: Prevention

Keywords: Atherosclerosis, Primary Prevention, Risk Assessment

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