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A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
Published on: March 6, 2018
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Intermittent Hormone Therapy Models Analysis and Bayesian Model Comparison for Prostate Cancer
S Pasetto1, H Enderling2,3,4, R A Gatenby2,5
1Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA. stefano.pasetto@moffitt.org.
Bulletin of Mathematical Biology
|November 19, 2021
Summary
Intermittent androgen deprivation therapy (ADT) for prostate cancer shows promise. Mathematical models help predict patient response and identify optimal treatment strategies by analyzing prostate-specific antigen (PSA) dynamics.
Area of Science:
- Urology
- Mathematical Oncology
- Computational Biology
Background:
- Prostate cancer treatment relies on androgen deprivation therapy (ADT).
- Continuous ADT faces challenges with cancer cell resistance.
- Intermittent ADT offers a potential alternative with reduced toxicity.
Purpose of the Study:
- To compare 13 mathematical models simulating intermittent ADT response.
- To assess model ability in describing prostate-specific antigen (PSA) dynamics.
- To identify models that best fit clinical data for prostate cancer patients.
Main Methods:
- Bayesian inference and model analysis applied to 13 intermittent dynamical models.
- Models calibrated using longitudinal PSA data from a clinical trial.
- Bayesian model comparison used to evaluate model evidence and likelihood.
Main Results:
- Identified models capable of distinguishing between relapsing and non-relapsing patients.
- Determined parameter intervals for potential clinical exploitation of critical points.
- Several models demonstrated strong ability to simulate patient-specific PSA dynamics.
Conclusions:
- Mathematical models are valuable tools for understanding intermittent ADT response in prostate cancer.
- Specific models show high potential for predicting patient outcomes and guiding treatment.
- Further analysis can refine model application for clinical decision-making in prostate cancer management.
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