JSM 2004 - Toronto

Abstract #302099

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Activity Number: 384
Type: Contributed
Date/Time: Wednesday, August 11, 2004 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #302099
Title: A Mixed Effects Model for Serial PSA Following Surgery in Men with Prostate Cancer
Author(s): Mousumi Banerjee*+ and Julie George
Companies: University of Michigan and Wayne State University
Address: Dept. of Biostatistics, Ann Arbor, MI, 48109,
Keywords: random effects ; longitudinal data ; serial PSA
Abstract:

Prostate cancer is more prevalent and causes more deaths in African Americans compared to Caucasian men. It is clinically useful to know when PSA levels first begin to rise rapidly after surgery, and to determine if the natural history of PSA progression post-surgery is different in the two races. Follow-up serial PSAs describe a dynamic evolution of the disease, and thus contain important information regarding progression. This article uses a piecewise nonlinear mixed-effects model to describe longitudinal changes in PSA in men after surgery. The model is linear after surgery and exponential nearer the time recurrence is detected. The time at which the PSAs change from linear to exponential phase is unknown but is estimated by including random terms that allow each subject to have his own transition time. The model also accounts for race, age, and stage. Various parameters are allowed to differ between the two races. Our analysis suggests that transition times are different for the two races, and Caucasians have a longer latency period than African Americans. This model may be useful in a variety of research settings where it is necessary to estimate the unknown time of an event.

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