title: Quantitative mathematical modeling of PSA dynamics of prostate cancer patients treated with intermittent androgen suppression.
abstract: If a mathematical model is to be used in the diagnosis, treatment, or prognosis of a disease, it must describe the inherent quantitative dynamics of the state. An ideal candidate disease is prostate cancer owing to the fact that it is characterized by an excellent biomarker, prostate-specific antigen (PSA), and also by a predictable response to treatment in the form of androgen suppression therapy. Despite a high initial response rate, the cancer will often relapse to a state of androgen independence which no longer responds to manipulations of the hormonal environment. In this paper, we present relevant background information and a quantitative mathematical model that potentially can be used in the optimal management of patients to cope with biochemical relapse as indicated by a rising PSA.
authors.affiliation: Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505,  Japan.
authors.forename: Yoshito
authors.initials: Y
authors.lastname: Hirata
authors.forename: Koichiro
authors.initials: K
authors.lastname: Akakura
authors.forename: Celestia S
authors.initials: CS
authors.lastname: Higano
authors.forename: Nicholas
authors.initials: N
authors.lastname: Bruchovsky
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Aihara
mesh_terms: D000726:Androgen Antagonists / Q000008:administration & dosage; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D009364:Neoplasm Recurrence, Local; D011379:Prognosis; D017430:Prostate-Specific Antigen / Q000378:metabolism*; D011471:Prostatic Neoplasms / Q000378:metabolism / Q000628:therapy*
chemical_list: D000726:Androgen Antagonists; D017430:Prostate-Specific Antigen