{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,11]],"date-time":"2026-11-11T01:44:15Z","timestamp":1794361455315,"version":"4.9.0"},"reference-count":17,"publisher":"American Medical Association (AMA)","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Cardiol"],"published-print":{"date-parts":[[2025,9,1]]},"abstract":"\n Importance<\/jats:title>\n In the original validation, the Predicting Risk of Cardiovascular Disease (CVD) Events (PREVENT) equations demonstrated good discrimination and calibration among racial and ethnic groups, but the model performance among Asian and Hispanic disaggregated subgroups has not been previously described.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To assess the performance of the PREVENT equations by race and ethnicity, including disaggregated Asian and Hispanic subgroups.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This was an electronic health record\u2013based retrospective cohort study of primary care patients aged 30 to 79 years across Sutter Health, a large integrated health system in Northern California, from January 2010 to September 2023. Patients who had at least 2 primary care visits during the study period were eligible for the study (1\u202f484\u202f582). Those outside of the study age range, with prior CVD events in the washout period, missing key predictors, or having at least 1 predictor out of the allowed normal range for the American Heart Association\u2019s PREVENT equations, were excluded, leaving a study population of 361\u202f778.<\/jats:p>\n <\/jats:sec>\n \n Exposure<\/jats:title>\n Eligible patients had complete baseline data required for the PREVENT equations, including non\u2013high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, body mass index, estimated glomerular filtration rate (or creatinine), diabetes, and current smoking status, and were free from CVD at baseline.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n \n The primary outcomes were CVD events, identified using\n International Classification of Diseases<\/jats:italic>\n ,\n Ninth<\/jats:italic>\n and\n Tenth Revisions<\/jats:italic>\n , codes described in the PREVENT derivation.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Among 361\u202f778 patients who met the inclusion criteria, mean (SD) age was 54.6 (12.2) years; 191\u202f151 (53%) were female; and 81\u202f424 (22%) were non-Hispanic Asian and 40\u202f897 (11%) were Hispanic. Over a mean (SD) follow-up of 8.1 (3.2) years, there were 22\u202f648 (6.3%) CVD events. The C statistic for total CVD was 0.83 (95% CI, 0.82-0.84) for the Asian population and 0.80 (95% CI, 0.79-0.81) for the Hispanic population. The calibration slopes were 0.84 (95% CI, 0.78-0.90) and 1.02 (95% CI, 0.94-1.10) for Asian and Hispanic patients, respectively. Within the Asian population, C statistics for total CVD among disaggregated Asian subgroups ranged from 0.79 (95% CI, 0.77-0.81) in Filipino patients to 0.85 (95% CI, 0.83-0.87) in Asian Indian patients. The calibration slope for total CVD was less than 1 for all Asian subgroups except Asian Indian. Among disaggregated Hispanic subgroups, the C statistics were similar and between 0.80 and 0.82 for total CVD, and the calibration slope for total CVD included 1 for all subgroups. There were small differences in the performance of atherosclerotic CVD and heart failure PREVENT equations among racial and ethnic groups and subgroups.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n The PREVENT equations appropriately predicted risk in contemporary diverse Asian and Hispanic subgroups with modest variation in performance across disaggregated subgroups.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamacardio.2025.1865","type":"journal-article","created":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T11:31:10Z","timestamp":1750851070000},"page":"876","source":"Crossref","is-referenced-by-count":37,"title":["Performance of the American Heart Association\u2019s PREVENT Equations Among Disaggregated Racial and Ethnic Subgroups"],"prefix":"10.1001","volume":"10","author":[{"given":"Xiaowei","family":"Yan","sequence":"first","affiliation":[{"name":"Center for Health Systems Research, Sutter Health, Walnut Creek, California"},{"name":"Palo Alto Medical Foundation Institute, Sutter Health, Palo Alto, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrian M.","family":"Bacong","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Medicine and the Cardiovascular Institute, School of Medicine, Stanford University, Stanford, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiwen","family":"Huang","sequence":"additional","affiliation":[{"name":"Center for Health Systems Research, Sutter Health, Walnut Creek, California"},{"name":"Palo Alto Medical Foundation Institute, Sutter Health, Palo Alto, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hannah","family":"Husby","sequence":"additional","affiliation":[{"name":"Center for Health Systems Research, Sutter Health, Walnut Creek, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramzi","family":"Dudum","sequence":"additional","affiliation":[{"name":"Division of Cardiology, University of California, San Francisco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Powell","family":"Jose","sequence":"additional","affiliation":[{"name":"Sutter Medical Group, Sutter Health, Sacramento, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Latha","family":"Palaniappan","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Medicine and the Cardiovascular Institute, School of Medicine, Stanford University, Stanford, California"},{"name":"Stanford Center for Asian Health Research and Education (CARE), Stanford University, Sacramento, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatima","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Medicine and the Cardiovascular Institute, School of Medicine, Stanford University, Stanford, California"},{"name":"Center for Digital Health, Stanford University School of Medicine, Sacramento, California"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10","reference":[{"issue":"11","key":"hoi250031r1","first-page":"e596","article-title":"2019 ACC\/AHA Guideline on the Primary Prevention of Cardiovascular Disease: a report of the American College of Cardiology\/American Heart Association Task Force on Clinical Practice Guidelines.","volume":"140","author":"Arnett","year":"2019","journal-title":"Circulation"},{"issue":"6","key":"hoi250031r2","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1161\/CIRCULATIONAHA.123.067626","article-title":"Development and validation of the American Heart Association\u2019s PREVENT 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Cardiovasc Qual Outcomes"},{"issue":"1","key":"hoi250031r14","doi-asserted-by":"crossref","first-page":"19475","DOI":"10.1038\/s41598-022-21878-x","article-title":"Racial disparities and prevalence of cardiovascular disease risk factors, cardiometabolic risk factors, and cardiovascular health metrics among US adults: NHANES 2011-2018.","volume":"12","author":"Lopez-Neyman","year":"2022","journal-title":"Sci Rep"},{"key":"hoi250031r15","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1038\/s41746-020-0304-9","article-title":"Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities.","volume":"3","author":"Paulus","year":"2020","journal-title":"NPJ Digit Med"},{"issue":"9","key":"hoi250031r16","doi-asserted-by":"crossref","first-page":"1976","DOI":"10.1161\/HYPERTENSIONAHA.124.22998","article-title":"Predicted cardiovascular Risk by the PREVENT equations in US adults with stage 1 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