title: A multivariate cure model for left-censored and right-censored data with application to colorectal cancer screening patterns.
abstract: We develop a multivariate cure survival model to estimate lifetime patterns of colorectal cancer screening. Screening data cover long periods of time, with sparse observations for each person. Some events may occur before the study begins or after the study ends, so the data are both left-censored and right-censored, and some individuals are never screened (the 'cured' population). We propose a multivariate parametric cure model that can be used with left-censored and right-censored data. Our model allows for the estimation of the time to screening as well as the average number of times individuals will be screened. We calculate likelihood functions based on the observations for each subject using a distribution that accounts for within-subject correlation and estimate parameters using Markov chain Monte Carlo methods. We apply our methods to the estimation of lifetime colorectal cancer screening behavior in the SEER-Medicare data set. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Department of Applied Mathematics, University of Colorado Boulder, Boulder, CO, U.S.A.
authors.forename: Yolanda C
authors.identifier: 0000-0003-2097-2838
authors.initials: YC
authors.lastname: Hagar
authors.affiliation: Department of Public Health Sciences, University of California, Davis, Davis, CA, U.S.A.
authors.forename: Danielle J
authors.initials: DJ
authors.lastname: Harvey
authors.affiliation: Department of Public Health Sciences, University of California, Davis, Davis, CA, U.S.A.
authors.forename: Laurel A
authors.initials: LA
authors.lastname: Beckett
mesh_terms: D015179:Colorectal Neoplasms / Q000175:diagnosis*; D055088:Early Detection of Cancer; D006801:Humans; D016013:Likelihood Functions; D008390:Markov Chains; D015233:Models, Statistical
keywords: SEER-Medicare; colorectal cancer; cure model; left-censoring; multivariate survival