title: Bayesian analysis of recurrent event with dependent termination: an application to a heart transplant study.
abstract: For a heart transplant patient, the risk of graft rejection and risk of death are likely to be associated. Two fully specified Bayesian models for recurrent events with dependent termination are applied to investigate the potential relationships between these two types of risk as well as association with risk factors. We particularly focus on the choice of priors, selection of the appropriate prediction model, and prediction methods for these two types of risk for an individual patient. Our prediction tools can be easily implemented and helpful to physicians for setting heart transplant patients' biopsy schedule.
authors.affiliation: Department of Neurological Sciences, Rush University Medical Center, 1725 W. Harrison St., Ste. 755, Chicago, IL 60612, USA. bichun_ouyang@rush.edu
authors.forename: Bichun
authors.initials: B
authors.lastname: Ouyang
authors.forename: Debajyoti
authors.initials: D
authors.lastname: Sinha
authors.forename: Elizabeth H
authors.initials: EH
authors.lastname: Slate
authors.forename: Adrian B
authors.initials: AB
authors.lastname: Van Bakel
mesh_terms: D001499:Bayes Theorem; D001706:Biopsy; D056808:Biostatistics / Q000379:methods*; D005260:Female; D006084:Graft Rejection / Q000175:diagnosis / Q000209:etiology; D016027:Heart Transplantation / Q000009:adverse effects / Q000401:mortality / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D015233:Models, Statistical; D012307:Risk Factors; D013269:Stochastic Processes