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Related Experiment Video

Updated: Aug 27, 2025

A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer

A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer

Published on: March 6, 2018

Modeling Disease Trajectories for Castration-resistant Prostate Cancer Using Nationwide Population-based Data.

Eugenio Ventimiglia^1,2, Anna Bill-Axelson¹, Jan Adolfsson³

¹Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

European Urology Open Science

|October 3, 2022

Summary

This summary is machine-generated.

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.

Keywords:

Castration-resistant prostate cancer State transition model Survival

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Last Updated: Aug 27, 2025

A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer

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Published on: March 6, 2018

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An Orthotopic Murine Model of Human Prostate Cancer Metastasis

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Published on: September 18, 2013

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.