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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
Prognostic Factor Analysis and Nomogram Development in Castration-Resistant Prostate Cancer with Visceral Metastases
Pengfei Xu1,2, Xianfu Lin2, Yunhai Zhu1
1Department of Urology, Shanghai Baoshan District Wusong Central Hospital, Shanghai, China.
Cancer Biotherapy & Radiopharmaceuticals
|July 30, 2026
Summary
A new six-factor nomogram identifies poor prognostic factors for castration-resistant prostate cancer (CRPC) with visceral metastases. This tool aids risk stratification but requires validation for radionuclide therapy selection.
Area of Science:
- Oncology
- Medical Imaging
- Biostatistics
Background:
- Castration-resistant prostate cancer (CRPC) with visceral metastases has a poor prognosis.
- Accurate prognostic tools are needed for risk stratification and treatment planning.
Purpose of the Study:
- To identify independent prognostic factors in CRPC patients with visceral metastases.
- To develop and validate a prognostic nomogram for individualized risk stratification.
- To generate a framework for selecting patients for radionuclide therapies.
Main Methods:
- Retrospective cohort study of 98 CRPC patients with visceral metastases.
- Collected demographics, tumor parameters, biomarkers, and treatment data.
- Used Kaplan-Meier analysis, Cox regression, and a six-factor prognostic nomogram; assessed with C-index and AUC.
Main Results:
- Identified six adverse prognostic factors for overall survival (OS): ECOG PS ≥2, multiorgan metastases, high alkaline phosphatase, low hemoglobin, low albumin, and low PSA decline.
- Median OS was 13.2 months, median PFS was 7.5 months.
- The nomogram showed good performance with a C-index of 0.712 for OS and 0.698 for PFS.
Conclusions:
- The six-factor nomogram provides a quantitative prognostic framework for CRPC patients with visceral metastases.
- This model is hypothesis-generating and requires prospective validation for radionuclide therapy selection (e.g., 177Lu-PSMA-617, 223Ra).
- Integration with molecular biomarkers is crucial for future validation and treatment guidance.