American Statistical Association
New York City
Metropolitan Area Chapter

Memorial Sloan-Kettering Cancer Center
Biostatistics Seminar

Jeremy Taylor
Department of Biostatistics
University of Michigan


For monitoring patients treated for prostate cancer with radiation therapy, Prostate Specific Antigen (PSA) is measured periodically after they receive treatment. Increases in PSA are suggestive of recurrence of the cancer and are used in making decisions about possible new treatments, such as salvage hormone therapy. The data from studies of such patients typically consist of longitudinal PSA measurements, censored event times, and baseline covariates. We develop a joint model to describe these combined longitudinal and survival data. In this model, the longitudinal PSA data follows a non-linear hierarchical mixed model. The clinical recurrences are modeled using a time-dependent proportional hazards model where the time dependent covariates include both the current value and the slope of post-treatment PSA profile. Estimates of the parameters in the model are obtained by Markov chain Monte Carlo (MCMC) techniques. One application of this model is to make individualized prediction of disease progression for censored and alive patients, based on all their available pre-treatment and follow-up data. Another application is to estimate the effect of salvage hormone therapy on reducing the risk of clinical recurrence. In this talk, I will discuss the data, the models, the estimation methods, the statistical issues and the individual prediction. (Website:

This is joint work with Menggang Yu, Donna Ankerst,
Cecile Proust-Lima, Ning Liu, Yongseok Park and Howard Sandler.

Date: Wednesday, September 16, 2009
Time: 4:00 - 5:00 P.M.
Location: Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
3rd Floor Conference Room
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.


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