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. Firstly, a likelihood based method using piecewise constant transition intensities under a Markov assumption. Secondly, a pseudo-likelihood method using inverse probability of tracing weights. For the breast cancer example, both methods improve the precision of estimates compared to a conventional approach based on excluding patients.