Home News General Health News PREVENT Equations Reclassify Half of U.S. Adults to Lower ASCVD Risk

PREVENT Equations Reclassify Half of U.S. Adults to Lower ASCVD Risk

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Considerable decrease estimated in U.S. adults receiving or recommended for preventive treatment with statins, antihypertensives

By Elana Gotkine HealthDay Reporter

FRIDAY, Aug. 2, 2024 (HealthDay News) — Use of the Predicting Risk of cardiovascular disease EVENTs (PREVENT) equations instead of the 2013 recommended pooled cohort equations for estimating the 10-year risk for atherosclerotic cardiovascular disease could result in a considerable decrease in the number of adults receiving or recommended for preventive treatment with statin or antihypertensive therapy, according to a study published online July 29 in the Journal of the American Medical Association.

James A. Diao, M.D., from Harvard Medical School in Boston, and colleagues estimated changes in risk categorization, treatment eligibility, or clinical outcomes when applying PREVENT equations to existing American College of Cardiology (ACC) and American Heart Association (AHA) guidelines. Data were included for a sample of 7,765 U.S. adults aged 30 to 79 years who participated in the National Health and Nutrition Examination Surveys from 2011 to March 2020.

The researchers estimated that using PREVENT equations would reclassify about half (53 percent) of U.S. adults to lower ACC and AHA risk categories and very few (0.41 percent) to higher risk categories. There would be an estimated decrease in the number of U.S. adults receiving or recommended for preventive treatment of 14.3 million for statin therapy and 2.62 million for antihypertensive therapy. These decreases could result in 107,000 additional occurrences of myocardial infarction or stroke over 10 years. The changes in eligibility would affect twice as many men as women and a greater proportion of Black than White adults.

“The magnitude of these projected changes warrants careful reconsideration of current treatment thresholds using decision-analytic or cost-effectiveness frameworks,” the authors write.

Several authors disclosed ties to the pharmaceutical industry.

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