Log in to MyACC
Validation of AHA PREVENT CVD Risk Equations
Quick Takes
- I was concerned but this validation of the recent AHA PREVENT CVD risk equation is very convincing.
- The limitation of the validation is that the endpoint was CVD mortality and not major CV events, which will likely be coming in the future.
- The inclusion of coronary calcium scores using MESA data that will soon be 20 years old may help with accurate prediction of nonfatal CV events.
Study Questions:
What are the prognostic capabilities, calibration, and discrimination of the American Heart Association’s (AHA) Predicting Risk of Cardiovascular Disease Events (PREVENT) equations in a cohort representative of the US population when compared to the Pooled Cohort Equations (PCEs)?
Methods:
This prognostic study used data from National Health and Nutrition Examination Survey (NHANES) 1999 to 2010 data cycles. Participants included adults with available 10-year follow-up data. Data curation and analyses took place from December 2023 through May 2024. Primary outcomes were risk estimated by the PREVENT equations compared to risk estimates from the PCEs defined as composite cardiovascular disease (CVD)-related mortality at 10 years of follow-up. Model discrimination was assessed with receiver-operator characteristic curves and Harrell C-statistic from proportional hazard regression; model calibration was determined as the slope of predicted versus observed risk.
Results:
The study cohort consisted of 172.9 million participants (mean age, 45.0 years [95% CI, 44.6-45.4 years]; 52.1% women [95% CI, 51.5%-52.6%]). When adjusted for the NHANES survey design, a 1% increase in PREVENT risk estimates was significantly associated with increased CVD mortality risk (hazard ratio, 1.090; 95% CI, 1.087-1.094). PREVENT risk scores demonstrated excellent discrimination (C-statistic, 0.890; 95% CI, 0.881-0.898) but moderate underfitting of the model (calibration slope, 1.13; 95% CI, 1.06-1.21). PREVENT risk models performed statistically significantly better than the PCEs, as assessed by the net reclassification index (0.093; 95% CI, 0.073-0.115). Sex-specific improvements in CVD death risk estimation were noted, suggesting that the PREVENT equations may better capture sex-based discrepancies in the incidence and impact of cardiometabolic disease.
Conclusions:
In this prognostic study of the PREVENT equations, risk estimates demonstrated excellent discrimination and only modest discrepancies in calibration. These findings provided evidence supporting utilization of the PREVENT equations for application in determining CVD deaths as suggested by the AHA.
Perspective:
PREVENT, the new AHA equation for primary prevention, uses traditional atherosclerotic CVD risk factors as well as 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 heart failure in US adults 30-79 years of age. To do so, PREVENT equations address changes in risk factor prevalence across multiple populations (total of 25 studies with >3 million participants), treatment with antihypertensives and statins and intervention approaches, and the rise in various CVD subtypes. In contrast, PCE uses risk enhancers and does not include risk of heart failure.
That each 1% increase in the PREVENT model was associated with an increase in observed risk of CV death >1% (i.e., underprediction) contrasts with the PCE model, which was overfit, indicating a degree of overprediction of risk. The authors also suggest cerebral small vessel disease and coronary artery calcification in future studies incorporating chronic conditions into the PREVENT risk estimation. The NHANES database is linked to the National Death Index, which allows for adjudication of mortality outcomes using International Classification of Diseases, Tenth Revision (ICD-10) codes. However, this limits the identification of nonfatal CVD events.
Clinical Topics: Prevention
Keywords: Atherosclerosis, Heart Disease Risk Factors, Primary Prevention, Risk Assessment
< Back to Listings
