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Related Concept Videos

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  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Nomogram-based Prognostic Model Construction For Progression To Castration-resistant Prostate Cancer In Patients With High Tumor Burden And Osseous Metastatic Prostate Cancer.
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Nomogram-based Prognostic Model Construction For Progression To Castration-resistant Prostate Cancer In Patients With High Tumor Burden And Osseous Metastatic Prostate Cancer.

Related Experiment Video

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

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Nomogram-based prognostic model construction for progression to castration-resistant prostate cancer in patients with high tumor burden and osseous metastatic prostate cancer.

Yiheng Huang1, Dan Yuan2, Rongfeng Zeng3

  • 1Department of Urology Surgery, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology Foshan 528200, Guangdong, China.

American Journal of Cancer Research
|October 17, 2024

View abstract on PubMed

Summary
This summary is machine-generated.
Keywords:
Prostate cancercastration-resistant prostate cancerneural invasionnomogram model

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This study developed a Nomogram model to predict castration-resistant prostate cancer (CRPC) progression in patients with high tumor burden and bone metastases. Key factors like neural invasion and PSA levels were identified, improving personalized treatment strategies.

Area of Science:

  • Urology
  • Medical Oncology
  • Prognostic Modeling

Background:

  • Prostate cancer (PCa) with high tumor burden (HTB) and osseous metastases faces challenges in predicting progression to castration-resistant prostate cancer (CRPC).
  • Accurate prognostic tools are crucial for timely intervention and personalized treatment strategies in advanced PCa patients.

Purpose of the Study:

  • To construct and validate a Nomogram model for predicting the risk of CRPC development.
  • To identify significant prognostic factors influencing CRPC progression in patients with HTB and osseous metastatic PCa.

Main Methods:

  • Retrospective analysis of 2018-2022 data from patients with HTB and osseous metastatic PCa.
  • Cox regression analysis to identify prognostic factors: neural invasion (NI), Gleason score, initial prostate-specific antigen (PSA), and lactate dehydrogenase (LDH).
prognostic factors
  • Nomogram model construction and validation using time-dependent receiver operating characteristic (ROC) curves and areas under the curves (AUCs).

    • Main Results:

    • Neural invasion (HR: 2.371), Gleason score (HR: 1.787), initial PSA (HR: 1.677), and LDH (HR: 2.729) were significant predictors of CRPC progression.
    • The Nomogram model demonstrated high accuracy for predicting one-year (AUC: 0.81) and two-year (AUC: 0.76) progression to CRPC.
    • External validation confirmed the model's robust predictive performance.

    Conclusions:

    • The developed Nomogram model accurately predicts CRPC progression in patients with advanced prostate cancer.
    • The model facilitates clinical decision-making and supports personalized treatment strategies for high-risk patients.
    • Identified prognostic factors offer insights into the mechanisms driving CRPC development in this population.