A tool developed by the American Heart Association (AHA), proven to accurately predict heart disease risk for Americans, can be applied to the global population, a new study led by NYU Langone Health shows.
Accurate identification of those at high cardiovascular disease (CVD) risk enables targeted use of preventive therapies, such as lipid-lowering medications and intensive blood pressure targets, and can move patients to quit smoking, eat better, and exercise, the study authors say.
The study addresses the AHA's risk-prediction tool, which is called Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) and was developed in partnership with NYU Grossman School of Medicine investigators. Published in 2023, PREVENT was designed to predict a person's 10- and 30-year total risk for CVD, time intervals long enough to include a meaningful amount of risk and treatment benefit. Total risk includes risk for heart failure along with the originally measured risks for heart attack and stroke because there are now effective therapies available that play into the prevention of all three conditions.
Use of the PREVENT tool to guide drug treatment, as well as in clinical trial design for people with hypertension and high cholesterol was recently incorporated for the first time into the treatment guidelines of several US medical societies based on studies that had included more than 6 million Americans. What was needed, say the authors, was strong evidence across a wide range of settings and clinical trials to support its adoption as part of clinical practice worldwide.
Publishing recently in Nature Medicine, the work found that the tool accurately predicted risk for cardiovascular disease among more than 6.4 million people from North America, Europe, Asia, and other regions. It was particularly effective for predicting heart failure and for patients at low-to-moderate risk, the group for whom flagging risk early can trigger treatment and lifestyle changes in time to avert severe disease. Adding a measure of kidney health made the predictions even more accurate.
"A key barrier to the international adoption of PREVENT is the uncertainty felt by physicians that the tool is generalizable across patient groups in different geographical areas," said senior study author Josef Coresh, MD, PhD , the founding director of the Optimal Aging Institute at NYU Langone. He is also the Terry and Mel Karmazin Professor in the Departments of Population Health and Medicine.
Most Effective Where It Matters
The study authors analysed data from 6.8 million patients that did not have cardiovascular disease at the beginning of 62 studies including 44 cohorts from North America, Europe, Asia, and 18 multi-regional randomized trials including 53,002 patients. The team was able to see how well predictions made by the tool at the study's start were borne out by comparing them with approximately 300,000 CVD events that participants experienced over the next 5.5 years.
For the study, researchers used discrimination and calibration, two fundamental metrics that evaluate the performance of disease risk prediction models. Discrimination measures how well a model separates patients who will go on to develop a disease from those who do not. In the current global analysis, PREVENT's discrimination was "superior," say the authors, in studies that focused on lower-risk patients, supporting the broader adoption of PREVENT in primary care populations, where some patients have very low risk and others have moderate-to-high risk leading to different treatment implications.
In terms of kidney health, the model's prediction performance improved when it accounted for a person's risk of albuminuria, a condition where urine protein levels are elevated due to kidney damage, often by high blood pressure or diabetes. In terms of discrimination, adding kidney risk to the PREVENT model brought about a statistically significant improvement in prediction accuracy.
Calibration measures how accurately the predicted probabilities match the actual outcomes for each patient down the road. Calibration measures for PREVENT were much better than those of an older model called Pooled Cohort Equation (PCE), which predicted risk of about half what it turned out to be.
"Because PREVENT guidelines are typically form the basis for national policies that guide treatment decisions, painstaking validation of PREVENT across diverse populations was critical," said Dr. Coresh. "Our large-scale study confirms that PREVENT is a reliable tool that can be used globally."
Along with Dr. Coresh, study authors from NYU Langone were Morgan Grams, MD, PhD, Yingying Sang, MSc, Shoshana Ballew, PhD, and Aditya Surapaneni, PhD.
The study was conducted by The Chronic Kidney Disease (CKD) Prognosis Consortium, which is funded in part by the grant R01DK100446 from the National Institute of Diabetes and Digestive and Kidney Diseases, part of the Nationals Institutes of Health. Also providing support was the US National Kidney Foundation
About NYU Langone Health
NYU Langone Health is a fully integrated health system that consistently achieves the best patient outcomes through a rigorous focus on quality that has resulted in some of the lowest mortality rates in the nation. Vizient Inc. has ranked NYU Langone No. 1 out of 118 comprehensive academic medical centers across the nation for four years in a row, and U.S. News & World Report recently ranked four of its clinical specialties No. 1 in the nation. NYU Langone offers a comprehensive range of medical services with one high standard of care across seven inpatient locations, its Perlmutter Cancer Center, and more than 320 outpatient locations in the New York area and Florida. The system also includes two tuition-free medical schools, in Manhattan and on Long Island, and a vast research enterprise.
