The standard approach of assessing long-term risk for atherosclerotic cardiovascular disease (ASCVD) works just as well for patients who are overweight as they do for patients at an optimal weight, according to a study by researchers from Yale and published in the JAMA Network Open.
Led by Dr Rohan Khera, an assistant professor of cardiovascular medicine at Yale, the team found that even among overweight and individuals with oibesity, using a calculator based on risk factors works well for most patients. They report that these findings support the use of pooled cohort equations (PCEs) as a risk prediction tool to guide prevention and treatment strategies in adults.
The PCEs were first introduced in 2013 to estimate an individual's risk of developing cardiovascular disease. Several patient characteristics including age, sex, race, smoking status, blood pressure levels, hypertension, diabetes, and cholesterol are factored into estimating their risk. The results are used as a guideline for prescribing medications or other primary prevention strategies to prevent cardiovascular disease.
The resulting study, ‘Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index’, was a pooled analysis of eight longitudinal cohort studies that included 37,311 adults without cardiovascular disease across obesity classes who were followed for ten years. The risk predicted by PCEs was compared against the patients' actual rate of developing cardiovascular disease.
In total, 360 individuals (1.0%) were in the underweight category, 9,937 (26.6%) were in the normal weight category, 13,601 (36.4%) were in the overweight category, 7,783 individuals (20.9%) had mild obesity and 5,630 individuals (15.1%) h moderate had to severe obesity. The median ten-year estimated ASCVD risk was 7.1% (2.5%-15.4%) and 3,709 individuals (9.9%) developed ASCVD over a median 10.8 years.
The PCE overestimated ASCVD risk in the overall cohort and across all BMI categories except the underweight category. Calibration was better near the clinical decision threshold in all BMI groups but worse among individuals with moderate or severe obesity and among those with the highest estimated ASCVD risk ≥20%. The PCE C statistic overall was 0.760, with lower discrimination in the moderate or severe obesity group vs with the normal-range BMI.
Waist circumference and hsCRP, but not BMI, were associated with increased ASCVD risk when added to the PCE. However, these factors did not improve model performance with or without added metrics.
These findings suggest that the PCE had acceptable model discrimination and were well calibrated at clinical decision thresholds but overestimated risk of ASCVD for individuals in overweight and obese categories, particularly individuals with high estimated risk. Incorporation of the usual clinical measures of obesity did not improve risk estimation of the PCE. Future research is needed to determine whether incorporation of alternative high-risk obesity markers (eg, weight trajectory or measures of visceral or ectopic fat) into the PCE may improve risk prediction.
“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,” the authors concluded.
"The implication of these observations is that clinical decisions regarding risk reduction therapies among most individuals with obesity should not factor in their weight," explained Khera.
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