Literature DB >> 21198137

Hybrid optimal scheduling for intermittent androgen suppression of prostate cancer.

Yoshito Hirata1, Mario di Bernardo, Nicholas Bruchovsky, Kazuyuki Aihara.   

Abstract

We propose a method for achieving an optimal protocol of intermittent androgen suppression for the treatment of prostate cancer. Since the model that reproduces the dynamical behavior of the surrogate tumor marker, prostate specific antigen, is piecewise linear, we can obtain an analytical solution for the model. Based on this, we derive conditions for either stopping or delaying recurrent disease. The solution also provides a design principle for the most favorable schedule of treatment that minimizes the rate of expansion of the malignant cell population.
© 2010 American Institute of Physics.

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Year:  2010        PMID: 21198137     DOI: 10.1063/1.3526968

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  11 in total

1.  Personalizing Androgen Suppression for Prostate Cancer Using Mathematical Modeling.

Authors:  Yoshito Hirata; Kai Morino; Koichiro Akakura; Celestia S Higano; Kazuyuki Aihara
Journal:  Sci Rep       Date:  2018-02-08       Impact factor: 4.379

2.  The parameter Houlihan: A solution to high-throughput identifiability indeterminacy for brutally ill-posed problems.

Authors:  David J Albers; Matthew E Levine; Lena Mamykina; George Hripcsak
Journal:  Math Biosci       Date:  2019-08-24       Impact factor: 2.144

Review 3.  Mathematically modelling and controlling prostate cancer under intermittent hormone therapy.

Authors:  Yoshito Hirata; Gouhei Tanaka; Nicholas Bruchovsky; Kazuyuki Aihara
Journal:  Asian J Androl       Date:  2012-01-09       Impact factor: 3.285

4.  A partial differential equation model and its reduction to an ordinary differential equation model for prostate tumor growth under intermittent hormone therapy.

Authors:  Youshan Tao; Qian Guo; Kazuyuki Aihara
Journal:  J Math Biol       Date:  2013-08-28       Impact factor: 2.259

5.  Quantitative mathematical modeling of PSA dynamics of prostate cancer patients treated with intermittent androgen suppression.

Authors:  Yoshito Hirata; Koichiro Akakura; Celestia S Higano; Nicholas Bruchovsky; Kazuyuki Aihara
Journal:  J Mol Cell Biol       Date:  2012-05-04       Impact factor: 6.216

6.  Population physiology: leveraging electronic health record data to understand human endocrine dynamics.

Authors:  D J Albers; George Hripcsak; Michael Schmidt
Journal:  PLoS One       Date:  2012-12-14       Impact factor: 3.240

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

Authors:  Yoshito Hirata; Kai Morino; Koichiro Akakura; Celestia S Higano; Nicholas Bruchovsky; Teresa Gambol; Susan Hall; Gouhei Tanaka; Kazuyuki Aihara
Journal:  PLoS One       Date:  2015-06-24       Impact factor: 3.240

8.  Dynamical phenotyping: using temporal analysis of clinically collected physiologic data to stratify populations.

Authors:  D J Albers; Noémie Elhadad; E Tabak; A Perotte; George Hripcsak
Journal:  PLoS One       Date:  2014-06-16       Impact factor: 3.240

9.  Personalized glucose forecasting for type 2 diabetes using data assimilation.

Authors:  David J Albers; Matthew Levine; Bruce Gluckman; Henry Ginsberg; George Hripcsak; Lena Mamykina
Journal:  PLoS Comput Biol       Date:  2017-04-27       Impact factor: 4.475

10.  Predicting disease progression from short biomarker series using expert advice algorithm.

Authors:  Kai Morino; Yoshito Hirata; Ryota Tomioka; Hisashi Kashima; Kenji Yamanishi; Norihiro Hayashi; Shin Egawa; Kazuyuki Aihara
Journal:  Sci Rep       Date:  2015-05-20       Impact factor: 4.379

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