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Risk-Estimation Tool Used to Guide Treatment Strategies May Overestimate ASCVD Risk in Obese Patients

November 04, 2020

By Julie Gould 

ian neelandIan J Neeland, MD, FAHA, department of medicine, University Hospitals Cleveland Medical Center, explains why the use of pooled cohort equations as a risk-estimation tool to guide prevention and treatment strategies in adults regardless of obesity status should be used, however, future studies will need to determine whether the use of more specific risk markers for obesity may improve estimation of ASCVD risk.

What existing data led you and your co-investigators to conduct this research?

The pooled cohort equations (PCE) were introduced in 2013 as sex- and race-specific tools for estimating 10-year absolute rates of atherosclerotic cardiovascular disease (ASCVD) events in a primary prevention population. The risk estimates were derived based on a combination of established cardiovascular risk factors examined prospectively in specific cohorts selected for derivation of the PCE.1 Variables included in the PCE are age, sex, race (ie, White, Black, or other), smoking status, systolic blood pressure, hypertension treatment status, diabetes status, and total and high-density lipoprotein (HDL) cholesterol levels. Risk estimates are then used to guide recommendations for preventive therapies (eg, lifestyle modification, statin medication, and antihypertensive therapies). Given the use of the PCE estimates for risk-stratification and risk modification strategies, it is critical to ensure that the equations perform adequately in diverse at-risk groups. However, when applied to diverse population samples, the performance of the PCE has varied, with evidence of acceptable calibration in broad clinical populations but overestimation in some and underestimation in other selected groups. The use of the PCE for individuals with obesity has not been adequately studied but has important implications for ASCVD prevention. 

Please briefly describe your study and its findings. Were any of the outcomes particularly surprising? 

We combined risk factor and incident ASCVD data from 8 large community-based cohort studies, including 5 contemporary cohorts not used in derivation of the PCE, to compare discrimination and calibration of the PCE among individuals across categories for body mass index (BMI; calculated asweight in kilograms divided by height in meters squared).We additionally examined the effects of adding obesity-related measures to the PCE for ASCVD risk estimation. This cohort study found that the PCE had acceptable model discrimination but overestimated risk of

ASCVD across the spectrum of BMI, except the underweight category, with better calibration near the decision threshold and less optimal calibration in the highest risk groups. Incorporation of usual clinical measures of obesity did not result in more accurate risk estimation compared with the standard PCE. The outcomes were not surprising since prior work has shown overestimation of the PCE at the extremes of risk. Furthermore, incorporation of BMI into the PCE did not appear to improve performance given the heterogeneous nature of BMI in obesity.  

What are the possible real-world applications of these findings in clinical practice?

This study has several clinical implications. First, our findings suggest that the PCE can be used for ASCVD risk estimation in most individuals with obesity and that it is not necessary to lower PCE risk thresholds for these individuals. Second, the observation that obesity metrics did not substantially improve performance of the PCE model does not exclude the possibility that PCE model performance could be improved by using obesity-related risk factors that more robustly reflect cardiometabolic risk (eg, imaging-based assessments of visceral fat) and that are not uniformly captured in most cohorts. Future studies will be needed to elucidate whether clinical assessment of body fat distribution or alternative biomarkers associated with obesity augment ASCVD risk estimation in contemporary populations. Third, although the additional obesity-related metrics evaluated in our study did not improve performance of the PCE for ASCVD risk estimation, our results should not be misinterpreted to suggest that obesity is benign and unimportant for ASCVD risk assessment. Higher BMI categories were associated with a significant trend for more prevalent ASCVD risk factors. In addition, obesity is clearly associated with excess prevalence of many other adverse health outcomes, and efforts to diagnose and treat it effectively are essential to improving population health. The most recent cholesterol and primary prevention guidelines consider metabolic syndrome, a consequence of obesity, a risk-enhancing factor to further inform the discussion regarding statin use in primary prevention. 

Is there anything else pertaining to your research and findings that you would like to add? 

These findings support the use of the PCE as a risk-estimation tool to guide prevention and treatment strategies in adults regardless of obesity status. Future studies will need to determine whether the use of more specific risk markers for obesity may improve estimation of ASCVD risk among the increasing number of people living with obesity.

About Dr Neeland:

Ian J. Neeland, MD, is director of cardiovascular prevention and co-director of the Center for Integrated and Novel Approaches in Vascular-Metabolic Disease for University Hospitals Harrington Heart & Vascular Institute. He is also an associate professor of medicine at Case Western Reserve University School of Medicine. He is a general cardiologist with special expertise in obesity, diabetes and cardiovascular disease.

Dr. Neeland earned his medical degree at Mount Sinai School of Medicine in New York City. He completed a residency in internal medicine and was chief medical resident at Emory University School of Medicine in Atlanta, and then completed a combined clinical and research fellowship in cardiovascular medicine at UT Southwestern Medical Center in Dallas. He also holds a certificate in translational medicine from Emory's Laney Graduate School. Certified by the American Board of Internal Medicine in both internal medicine and cardiovascular diseases, he also holds a subspecialty certification in adult echocardiography from the National Board of Echocardiography.

Dr. Neeland is an active clinical and translational investigator with funding from the National Institutes of Health and industry. He has published over 80 scholarly articles and delivered a number of national, international and regionally invited lectures. He is a reviewer for many respected journals, including Circulation, for which he currently serves as an associate editor and section editor for Bridging Disciplines.

Dr. Neeland is a Fellow of the American Heart Association and serves on several national committees with the American Heart Association. Dr. Neeland is a member of professional organizations that include the AHA Council on Epidemiology and Prevention and the Council on Lifestyle and Cardiometabolic Health; American College of Cardiology; and American Society for Preventive Cardiology.


Khera R, Pandey A, Ayers CR, et al. Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index. JAMA Netw Open. 2020;3(10):e2023242. Published 2020 Oct 1. doi:10.1001/jamanetworkopen.2020.23242

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