title: Accounting for bias due to a non-ignorable tracing mechanism in a retrospective breast cancer cohort study.
abstract: We consider the analysis of competing risks in a retrospective breast cancer cohort study where tracing of patients is dependent on survival to a pre-specified truncation time. We demonstrate that if ignored, the observed cause-specific hazards will become distorted before the truncation time. Two approaches to account for the tracing bias are considered. First, a likelihood-based method using piecewise constant transition intensities under a Markov assumption. Second, a pseudo-likelihood method using inverse probability of tracing weights. For the breast cancer example, both methods improve the precision of estimates compared with a conventional approach based on excluding patients.
authors.affiliation: Department of Mathematics and Statistics, Lancaster University, U.K. a.titman@lancaster.ac.uk
authors.forename: Andrew C
authors.initials: AC
authors.lastname: Titman
authors.forename: Gillian A
authors.initials: GA
authors.lastname: Lancaster
authors.forename: Katie
authors.initials: K
authors.lastname: Carmichael
authors.forename: Diane
authors.initials: D
authors.lastname: Scutt
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015982:Bias; D001943:Breast Neoplasms / Q000453:epidemiology*; D015331:Cohort Studies; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D016013:Likelihood Functions; D008390:Markov Chains; D008875:Middle Aged; D012189:Retrospective Studies