Bart S Ferket1, Bob J H van Kempen1, Renske G Wieberdink1, Ewout W Steyerberg1, Peter J Koudstaal1, Albert Hofman1, Eyal Shahar1, Rebecca F Gottesman1, Wayne Rosamond1, Jorge R Kizer1, Richard A Kronmal1, Bruce M Psaty1, W T Longstreth1, Thomas Mosley1, Aaron R Folsom1, M G Myriam Hunink1, M Arfan Ikram2. 1. From the Departments of Epidemiology (B.S.F., B.J.H.v.K., R.G.W., A.H., M.G.M.H., M.A.I.), Radiology (B.S.F., B.J.H.v.K., M.G.M.H., M.A.I.), Neurology (R.G.W., P.J.K., M.A.I.), and Public Health (E.W.S.), Erasmus Medical Center, Rotterdam, the Netherlands; Division of Epidemiology and Biostatistics (E.S.), Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson; Department of Neurology (R.F.G.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Epidemiology (W.R.), Gillings School of Global Public Health, University of North Carolina, Chapel Hill; Department of Medicine, and Department of Epidemiology of Population Health (J.R.K.), Albert Einstein College of Medicine, Bronx, NY; Departments of Biostatistics (R.A.K.), Neurology (W.T.L.), and Epidemiology (W.T.L.), and Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Washington, Seattle; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Departments of Medicine (Geriatrics) and Neurology (T.M.), University of Mississippi Medical Center, Jackson; Division of Epidemiology and Community Health (A.R.F.), University of Minnesota, Minneapolis; and Department of Health Policy and Management (M.G.M.H.), Harvard School of Public Health, Boston, MA. 2. From the Departments of Epidemiology (B.S.F., B.J.H.v.K., R.G.W., A.H., M.G.M.H., M.A.I.), Radiology (B.S.F., B.J.H.v.K., M.G.M.H., M.A.I.), Neurology (R.G.W., P.J.K., M.A.I.), and Public Health (E.W.S.), Erasmus Medical Center, Rotterdam, the Netherlands; Division of Epidemiology and Biostatistics (E.S.), Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson; Department of Neurology (R.F.G.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Epidemiology (W.R.), Gillings School of Global Public Health, University of North Carolina, Chapel Hill; Department of Medicine, and Department of Epidemiology of Population Health (J.R.K.), Albert Einstein College of Medicine, Bronx, NY; Departments of Biostatistics (R.A.K.), Neurology (W.T.L.), and Epidemiology (W.T.L.), and Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Washington, Seattle; Group Health Research Institute (B.M.P.), Group Health Cooperative, Seattle, WA; Departments of Medicine (Geriatrics) and Neurology (T.M.), University of Mississippi Medical Center, Jackson; Division of Epidemiology and Community Health (A.R.F.), University of Minnesota, Minneapolis; and Department of Health Policy and Management (M.G.M.H.), Harvard School of Public Health, Boston, MA. m.a.ikram@erasmusmc.nl.
Abstract
OBJECTIVES: To develop and validate 10-year cumulative incidence functions of intracerebral hemorrhage (ICH) and ischemic stroke (IS). METHODS: We used data on 27,493 participants from 3 population-based cohort studies: the Atherosclerosis Risk in Communities Study, median age 54 years, 45% male, median follow-up 20.7 years; the Rotterdam Study, median age 68 years, 38% male, median follow-up 14.3 years; and the Cardiovascular Health Study, median age 71 years, 41% male, median follow-up 12.8 years. Among these participants, 325 ICH events, 2,559 IS events, and 9,909 nonstroke deaths occurred. We developed 10-year cumulative incidence functions for ICH and IS using stratified Cox regression and competing risks analysis. Basic models including only established nonlaboratory risk factors were extended with diastolic blood pressure, total cholesterol/high-density lipoprotein cholesterol ratio, body mass index, waist-to-hip ratio, and glomerular filtration rate. The cumulative incidence functions' performances were cross-validated in each cohort separately by Harrell C-statistic and calibration plots. RESULTS: High total cholesterol/high-density lipoprotein cholesterol ratio decreased the ICH rates but increased IS rates (p for difference across stroke types <0.001). For both the ICH and IS models, C statistics increased more by model extension in the Atherosclerosis Risk in Communities and Cardiovascular Health Study cohorts. Improvements in C statistics were reproduced by cross-validation. Models were well calibrated in all cohorts. Correlations between 10-year ICH and IS risks were moderate in each cohort. CONCLUSIONS: We developed and cross-validated cumulative incidence functions for separate prediction of 10-year ICH and IS risk. These functions can be useful to further specify an individual's stroke risk.
OBJECTIVES: To develop and validate 10-year cumulative incidence functions of intracerebral hemorrhage (ICH) and ischemic stroke (IS). METHODS: We used data on 27,493 participants from 3 population-based cohort studies: the Atherosclerosis Risk in Communities Study, median age 54 years, 45% male, median follow-up 20.7 years; the Rotterdam Study, median age 68 years, 38% male, median follow-up 14.3 years; and the Cardiovascular Health Study, median age 71 years, 41% male, median follow-up 12.8 years. Among these participants, 325 ICH events, 2,559 IS events, and 9,909 nonstroke deaths occurred. We developed 10-year cumulative incidence functions for ICH and IS using stratified Cox regression and competing risks analysis. Basic models including only established nonlaboratory risk factors were extended with diastolic blood pressure, total cholesterol/high-density lipoprotein cholesterol ratio, body mass index, waist-to-hip ratio, and glomerular filtration rate. The cumulative incidence functions' performances were cross-validated in each cohort separately by Harrell C-statistic and calibration plots. RESULTS: High total cholesterol/high-density lipoprotein cholesterol ratio decreased the ICH rates but increased IS rates (p for difference across stroke types <0.001). For both the ICH and IS models, C statistics increased more by model extension in the Atherosclerosis Risk in Communities and Cardiovascular Health Study cohorts. Improvements in C statistics were reproduced by cross-validation. Models were well calibrated in all cohorts. Correlations between 10-year ICH and IS risks were moderate in each cohort. CONCLUSIONS: We developed and cross-validated cumulative incidence functions for separate prediction of 10-year ICH and IS risk. These functions can be useful to further specify an individual's stroke risk.
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