Mathematical modeling of continuous and intermittent androgen suppression for the treatment of advanced prostate cancer
| Autor: | John G. Alford, Edward W. Swim, Alacia M. Voth |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Male
0301 basic medicine Oncology medicine.medical_specialty Time Factors Androgen suppression Models Biological Androgen deprivation therapy 03 medical and health sciences Prostate cancer 0302 clinical medicine Prostate Internal medicine Humans Medicine Computer Simulation Adverse effect business.industry Applied Mathematics Prostatic Neoplasms Cancer Androgen Antagonists General Medicine medicine.disease Clinical trial Sexual hormones Computational Mathematics 030104 developmental biology medicine.anatomical_structure 030220 oncology & carcinogenesis Modeling and Simulation Neoplasm Recurrence Local General Agricultural and Biological Sciences business |
| Zdroj: | Mathematical Biosciences and Engineering. 14:777-804 |
| ISSN: | 1551-0018 |
| DOI: | 10.3934/mbe.2017043 |
| Popis: | Prostate cancer is one of the most prevalent types of cancer among men. It is stimulated by the androgens, or male sexual hormones, which circulate in the blood and diffuse into the tissue where they stimulate the prostate tumor to grow. One of the most important treatments for advanced prostate cancer has become androgen deprivation therapy (ADT). In this paper we present three different models of ADT for prostate cancer: continuous androgen suppression (CAS), intermittent androgen suppression (IAS), and periodic androgen suppression. Currently, many patients in the U.S. receive CAS therapy of ADT, but many undergo a relapse after several years and experience adverse side effects while receiving treatment. Some clinical studies have introduced various IAS regimens in order to delay the time to relapse, and/or to reduce the economic costs and adverse side effects. We will compute and analyze parameter sensitivity analysis for CAS and IAS which may give insight to plan effective data collection in a future clinical trial. Moreover, a periodic model for IAS is used to develop an analytical formulation for relapse times which then provides information about the sensitivity of relapse to the parameters in our models. |
| Databáze: | OpenAIRE |
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