title: BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER'S DISEASE.
abstract: The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer's disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM.
authors.affiliation: Departments of Statistics and Operation Research, Biostatistics, and Psychology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
authors.forename: Eunjee
authors.initials: E
authors.lastname: Lee
authors.affiliation: Departments of Statistics and Operation Research, Biostatistics, and Psychology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
authors.forename: Hongtu
authors.initials: H
authors.lastname: Zhu
authors.affiliation: Departments of Statistics and Operation Research, Biostatistics, and Psychology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
authors.forename: Dehan
authors.initials: D
authors.lastname: Kong
authors.affiliation: School of Computing, Informatics, and Decision Systems Engineering Arizona State University Tempe, AZ 85287-8809 ylwang@asu.edu.
authors.forename: Yalin
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Departments of Statistics and Operation Research, Biostatistics, and Psychology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
authors.forename: Kelly Sullivan
authors.initials: KS
authors.lastname: Giovanello
authors.affiliation: Departments of Statistics and Operation Research, Biostatistics, and Psychology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Ibrahim
keywords: Alzheimer’s disease; functional principal component analysis; hippocampus surface morphology; mild cognitive impairment; proportional hazard model