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Updated: Aug 27, 2025
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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
13.2K
Modeling Disease Trajectories for Castration-resistant Prostate Cancer Using Nationwide Population-based Data
Eugenio Ventimiglia1,2, Anna Bill-Axelson1, Jan Adolfsson3
1Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
European Urology Open Science
|October 3, 2022
Summary
Disease trajectories for men with castration-resistant prostate cancer (CRPC) vary significantly. A new model accurately estimates time spent in the CRPC state, ranging from 1 to 4 years based on risk category.
Area of Science:
- Oncology
- Biostatistics
- Health Informatics
Background:
- Limited understanding of disease progression in castration-resistant prostate cancer (CRPC).
- Need for accurate prognostic models for CRPC patient management.
Purpose of the Study:
- Develop a state transition model to estimate CRPC duration and outcomes.
- Validate model predictions against real-world data.
Main Methods:
- Utilized population-based prostate-specific antigen (PSA) data from Sweden.
- Linked PSA data with nationwide health databases for comprehensive analysis.
- Compared observed cumulative incidence with model-predicted transitions.
Main Results:
- Estimated time in CRPC state varied from 1.1 years (high-risk) to 3.9 years (low-risk).
- 10-year prostate cancer mortality ranged from 93% (high-risk) to 54% (low-risk).
- Model demonstrated good agreement with observed population data.
Conclusions:
- Significant variation exists in CRPC disease duration based on risk stratification.
- The developed model accurately predicts disease trajectories and duration for CRPC patients.
