title: Prediction of coronary artery disease risk based on multiple longitudinal biomarkers.
abstract: In the last decade, few topics in the area of cardiovascular disease (CVD) research have received as much attention as risk prediction. One of the well-documented risk factors for CVD is high blood pressure (BP). Traditional CVD risk prediction models consider BP levels measured at a single time and such models form the basis for current clinical guidelines for CVD prevention. However, in clinical practice, BP levels are often observed and recorded in a longitudinal fashion. Information on BP trajectories can be powerful predictors for CVD events. We consider joint modeling of time to coronary artery disease and individual longitudinal measures of systolic and diastolic BPs in a primary care cohort with up to 20 years of follow-up. We applied novel prediction metrics to assess the predictive performance of joint models. Predictive performances of proposed joint models and other models were assessed via simulations and illustrated using the primary care cohort.
authors.affiliation: Eli Lilly and Company, Indianapolis, IN, 46285, U.S.A.
authors.forename: Lili
authors.initials: L
authors.lastname: Yang
authors.affiliation: Department of Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Population Health, Madison, Wisconsin.
authors.forename: Menggang
authors.initials: M
authors.lastname: Yu
authors.affiliation: Department of Biostatistics, Indiana University School of Medicine, 410 W. 10th Street Suite 3000, Indianapolis, IN, 46202-3002, U.S.A.
authors.forename: Sujuan
authors.initials: S
authors.lastname: Gao
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D015415:Biomarkers; D056808:Biostatistics; D001794:Blood Pressure; D015331:Cohort Studies; D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000209:etiology* / Q000503:physiopathology; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009010:Monte Carlo Method; D011237:Predictive Value of Tests; D011320:Primary Health Care; D012307:Risk Factors; D016019:Survival Analysis; D013997:Time Factors
chemical_list: D015415:Biomarkers
keywords: AARD; AUC; MRD; joint models; multiple longitudinal outcomes; prediction; time-to-event outcome