Analysis of prostate specific antigen "trajectories" : statistical challenges

Prostate Specific Antigen (PSA) is a biochemical marker used to monitor prostate cancer following treatment. We have analyzed serial PSA data for a cohort of men who underwent radical surgery for prostate cancer in the early 1990s. We first describe the development of a statistical model that reflects the characteristics of these data. It accommodates, via a mixture model with constrained parameters, two sub-populations of men who are and are not cured, along with the biologic pattern in the latter. We then describe how we fit this model using Gibbs Sampling. We describe how the output can be converted into parameters of interest to patients and their physicians