Accounting for bias due to a non-ignorable tracing mechanism in a retrospective breast cancer cohort study



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. Copyright © 2010 John Wiley & Sons, Ltd.