Intermittent Androgen Suppression: Estimating Parameters for Individual Patients Based on Initial PSA Data in Response to Androgen Deprivation Therapy

When a physician decides on a treatment and its schedule for a specific patient, information gained from prior patients and experience in the past is taken into account. A more objective way to make such treatment decisions based on actual data would be useful to the clinician.

Although there are many mathematical models proposed for various diseases, so far there is no mathematical method that accomplishes optimization of the treatment schedule using the information gained from past patients or "rapid learning" technology. In an attempt to use this approach, we integrate the information gained from patients previously treated with intermittent androgen suppression (IAS) with that from a current patient by first fitting the time courses of clinical data observed from the previously treated patients, then constructing the prior information of the parameter values of the mathematical model, and finally, maximizing the posterior probability for the parameters of the current patient using the prior information. Although we used data from prostate cancer patients, the proposed method is general, and thus can be applied to other diseases once an appropriate mathematical model is established for that disease.

PloS one. 2015 Jun 24*** epublish ***

Yoshito Hirata, Kai Morino, Koichiro Akakura, Celestia S Higano, Nicholas Bruchovsky, Teresa Gambol, Susan Hall, Gouhei Tanaka, Kazuyuki Aihara

Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo 153-8505, Japan; Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. , Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. , Department of Urology, JCHO Tokyo Shinjuku Medical Center, Japan Community Health Care Organization Tokyo, Japan. , Department of Medicine, University of Washington and Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. , Vancouver Prostate Centre, Vancouver, BC, Canada. , Department of Medicine, University of Washington and Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. , Department of Medicine, University of Washington and Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. , Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo 153-8505, Japan; Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan; Graduate School of Engineering, The University of Tokyo, Tokyo, Japan. , Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo 153-8505, Japan; Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan; Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.

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