ArticleJournal of the Royal Society, Interface2019
Mechanistic modelling of prostate-specific antigen dynamics shows potential for personalized prediction of radiation therapy outcome.
Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 28 citations in OpenAlex.
- Measurable imaging-based changes in enhancement of intrahepatic cholangiocarcinoma after radiotherapy reflect physical mechanisms of response.NPJ systems biology and applications · 2025Article
- Systems biology successes and areas for opportunity in prostate cancer.Endocrine-related cancer · 2025Review
- Physics-informed machine learning digital twin for reconstructing prostate cancer tumor growth via PSA tests.NPJ digital medicine · 2025Article
- Validating the predictions of mathematical models describing tumor growth and treatment response.ArXiv · 2025Article
- Patient-specific prostate tumour growth simulation: a first step towards the digital twin.Frontiers in physiology · 2024Article
- PersonalisedFrontiers in physiology · 2024Article
- Predicting regrowth of low-grade gliomas after radiotherapy.PLoS computational biology · 2023Article
- Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse.iScience · 2022Article
- High Accuracy Indicators of Androgen Suppression Therapy Failure for Prostate Cancer-A Modeling Study.Cancers · 2022Article
- Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology.Biophysics reviews · 2022Review
- Intermittent radiotherapy as alternative treatment for recurrent high grade glioma: a modeling study based on longitudinal tumor measurements.Scientific reports · 2021Article
- Evolutionary dynamics at the tumor edge reveal metabolic imaging biomarkers.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology.iScience · 2020Review
- Bayesian Information-Theoretic Calibration of Radiotherapy Sensitivity Parameters for Informing Effective Scanning Protocols in Cancer.Journal of clinical medicine · 2020Article
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Authors and funding
6 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
External beam radiation therapy is a widespread treatment for prostate cancer. The ensuing patient follow-up is based on the evolution of the prostate-specific antigen (PSA). Serum levels of PSA decay due to the radiation-induced death of tumour cells and cancer recurrence usually manifest as a rising PSA. The current definition of biochemical relapse requires that PSA reaches nadir and starts increasing, which delays the use of further treatments. Also, these methods do not account for the post-radiation tumour dynamics that may contain early information on cancer recurrence. Here, we develop three mechanistic models of post-radiation PSA evolution. Our models render superior fits of PSA data in a patient cohort and provide a biological justification for the most common empirical formulation of PSA dynamics. We also found three model-based prognostic variables: the proliferation rate of the survival fraction, the ratio of radiation-induced cell death rate to the survival proliferation rate, and the time to PSA nadir since treatment termination. We argue that these markers may enable the early identification of biochemical relapse, which would permit physicians to subsequently adapt patient monitoring to optimize the detection and treatment of cancer recurrence.
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