ArticleJournal of molecular cell biology2012
Quantitative mathematical modeling of PSA dynamics of prostate cancer patients treated with intermittent androgen suppression.
Article in Journal of molecular cell biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed.
- Estimating the Optimal Time to Perform a Positron Emission Tomography With Prostate-Specific Membrane Antigen in Prostatectomized Patients, Based on Data From Clinical Practice.Biometrical journal. Biometrische Zeitschrift · 2025Article
- Article
- Modeling the Human Bone-Tumor Niche: Reducing and Replacing the Need for Animal Data.JBMR plus · 2020Review
- Massive computational acceleration by using neural networks to emulate mechanism-based biological models.Nature communications · 2019Article
- PAGE4 and Conformational Switching: Insights from Molecular Dynamics Simulations and Implications for Prostate Cancer.Journal of molecular biology · 2018Article
- Personalizing Androgen Suppression for Prostate Cancer Using Mathematical Modeling.Scientific reports · 2018Article
- A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study.Journal of theoretical biology · 2017Article
- Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated With Eribulin.CPT: pharmacometrics & systems pharmacology · 2015Article
- Predicting disease progression from short biomarker series using expert advice algorithm.Scientific reports · 2015Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.