Ervin R Fox1, Tandaw E Samdarshi1, Solomon K Musani2, Michael J Pencina3, Jung Hye Sung4, Alain G Bertoni5, Vanessa Xanthakis6, Pelbreton C Balfour7, Satya S Shreenivas8, Carolyn Covington9, Philip R Liebson10, Daniel F Sarpong11, Kenneth R Butler12, Thomas H Mosley12, Wayne D Rosamond13, Aaron R Folsom14, David M Herrington7, Ramachandran S Vasan15, Herman A Taylor16. 1. Division of Cardiovascular Diseases, Department of Medicine, University of Mississippi Medical Center, Jackson. 2. Department of Medicine, Jackson Heart Study, University of Mississippi Medical Center, Jackson. 3. Department of Biostatistics and Bioinformatics, Duke Clinical Research Institute, Durham, North Carolina. 4. Department of Epidemiology, School of Public Health, Jackson State University, Jackson, Mississippi. 5. Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina. 6. Division of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts. 7. Division of Cardiology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina. 8. Division of Cardiovascular Health and Disease, Department of Medicine, University of Cincinnati, Cincinnati, Ohio. 9. School of Nursing, Howard University, Washington, DC. 10. Department of Preventive Medicine, Rush University Medical Center, Chicago, Illinois. 11. Center of Minority Health and Health Disparities, College of Pharmacy, Xavier University, New Orleans, Louisiana. 12. Division of Geriatrics, Department of Medicine, University of Mississippi Medical Center, Jackson. 13. Department of Epidemiology, The University of North Carolina at Chapel Hill. 14. Division of Epidemiology and Community Health, University of Minnesota, Minneapolis. 15. Division of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts15Division of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts. 16. Cardiovascular Research Institute, Department of Medicine, Morehouse School of Medicine, Atlanta, Georgia.
Abstract
IMPORTANCE: Cardiovascular risk assessment is a fundamental component of prevention of cardiovascular disease (CVD). However, commonly used prediction models have been formulated in primarily or exclusively white populations. Whether risk assessment in black adults is dissimilar to that in white adults is uncertain. OBJECTIVES: To develop and validate risk prediction models for CVD incidence in black adults, incorporating standard risk factors, biomarkers, and subclinical disease. DESIGN, SETTING, AND PARTICIPANTS: The Jackson Heart Study (JHS), a longitudinal community-based study of 5301 black adults in Jackson, Mississippi. Inclusive study dates were the date of a participant's first visit (September 2000 to March 2004) to December 31, 2011. The median (75th percentile) follow-up was 9.1 (9.7) years. The dates of the analysis were August 2013 to May 2015. Measurements included standard risk factors, including age, sex, body mass index, systolic and diastolic blood pressure, ratio of fasting total cholesterol to high-density lipoprotein cholesterol, estimated glomerular filtration rate, antihypertensive therapy, diabetes mellitus, and smoking; blood biomarkers; and subclinical disease measures, including ankle-brachial index, carotid intimal-medial thickness, and echocardiographic left ventricular hypertrophy and systolic dysfunction. MAIN OUTCOMES AND MEASURES: Incident CVD event was defined as the first occurrence of myocardial infarction, coronary heart disease death, congestive heart failure, stroke, incident angina, or intermittent claudication. Model performance was compared with the American College of Cardiology/American Heart Association (ACC/AHA) CVD risk algorithm and the Framingham Risk Score (FHS) refitted to the JHS data and evaluated in the Atherosclerosis Risk in Communities (ARIC) and Multi-Ethnic Study of Atherosclerosis cohorts. RESULTS: The study cohort comprised 3689 participants with mean (SD) age at baseline was 53 (11) years, and 64.8% (n = 2390) were female. Over a median of 9.1 years, 270 participants (166 women) experienced a first CVD event. A simple combination of standard CVD risk factors, B-type natriuretic peptide, and ankle-brachial index (model 6) yielded modest improvement over a model without B-type natriuretic peptide and ankle-brachial index (C statistic, 0.79; 95% CI, 0.75-0.83 [relative integrated discrimination improvement, 0.22; 95% CI, 0.15-0.30]). However, the reclassification improvement was not substantially different between model 6 and the ACC/AHA CVD Pooled Cohort risk equations or between model 6 and the FHS. The models discriminated reasonably well in the ARIC and Multi-Ethnic Study of Atherosclerosis data (C statistic range, 0.70-0.77). CONCLUSIONS AND RELEVANCE: Our findings using the JHS data in the present study are valuable because they confirm that current FHS and ACC/AHA risk algorithms work well in black individuals and are not easily improved on. A unique risk calculator for black adults may not be necessary.
IMPORTANCE: Cardiovascular risk assessment is a fundamental component of prevention of cardiovascular disease (CVD). However, commonly used prediction models have been formulated in primarily or exclusively white populations. Whether risk assessment in black adults is dissimilar to that in white adults is uncertain. OBJECTIVES: To develop and validate risk prediction models for CVD incidence in black adults, incorporating standard risk factors, biomarkers, and subclinical disease. DESIGN, SETTING, AND PARTICIPANTS: The Jackson Heart Study (JHS), a longitudinal community-based study of 5301 black adults in Jackson, Mississippi. Inclusive study dates were the date of a participant's first visit (September 2000 to March 2004) to December 31, 2011. The median (75th percentile) follow-up was 9.1 (9.7) years. The dates of the analysis were August 2013 to May 2015. Measurements included standard risk factors, including age, sex, body mass index, systolic and diastolic blood pressure, ratio of fasting total cholesterol to high-density lipoprotein cholesterol, estimated glomerular filtration rate, antihypertensive therapy, diabetes mellitus, and smoking; blood biomarkers; and subclinical disease measures, including ankle-brachial index, carotid intimal-medial thickness, and echocardiographic left ventricular hypertrophy and systolic dysfunction. MAIN OUTCOMES AND MEASURES: Incident CVD event was defined as the first occurrence of myocardial infarction, coronary heart disease death, congestive heart failure, stroke, incident angina, or intermittent claudication. Model performance was compared with the American College of Cardiology/American Heart Association (ACC/AHA) CVD risk algorithm and the Framingham Risk Score (FHS) refitted to the JHS data and evaluated in the Atherosclerosis Risk in Communities (ARIC) and Multi-Ethnic Study of Atherosclerosis cohorts. RESULTS: The study cohort comprised 3689 participants with mean (SD) age at baseline was 53 (11) years, and 64.8% (n = 2390) were female. Over a median of 9.1 years, 270 participants (166 women) experienced a first CVD event. A simple combination of standard CVD risk factors, B-type natriuretic peptide, and ankle-brachial index (model 6) yielded modest improvement over a model without B-type natriuretic peptide and ankle-brachial index (C statistic, 0.79; 95% CI, 0.75-0.83 [relative integrated discrimination improvement, 0.22; 95% CI, 0.15-0.30]). However, the reclassification improvement was not substantially different between model 6 and the ACC/AHA CVD Pooled Cohort risk equations or between model 6 and the FHS. The models discriminated reasonably well in the ARIC and Multi-Ethnic Study of Atherosclerosis data (C statistic range, 0.70-0.77). CONCLUSIONS AND RELEVANCE: Our findings using the JHS data in the present study are valuable because they confirm that current FHS and ACC/AHA risk algorithms work well in black individuals and are not easily improved on. A unique risk calculator for black adults may not be necessary.
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