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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. Establishment And Evaluation Of A Prognostic Model For Patients With Unresectable Gastric Cancer Liver Metastases

Establishment and evaluation of a prognostic model for patients with unresectable gastric cancer liver metastases

Zheng-Yao Chang1, Wen-Xing Gao1, Yue Zhang2

  • 1Department of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.

World Journal of Clinical Cases
|May 29, 2024

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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
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Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones
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Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones

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View abstract on PubMed

Summary
This summary is machine-generated.

This study identified key prognostic factors for gastric cancer with liver metastases (GCLM) and developed a nomogram to predict patient survival. The model shows promising accuracy for personalized outcome assessment.

Area of Science:

  • Oncology
  • Surgical Oncology
  • Medical Statistics

Background:

  • Liver metastases (LM) are a primary cause of poor outcomes in gastric cancer (GC).
  • Accurate prognosis prediction is crucial for managing patients with GCLM.

Purpose of the Study:

  • To identify significant prognostic risk factors for GCLM.
  • To develop and validate a nomogram for predicting individualized prognosis in GCLM patients.

Main Methods:

  • Retrospective analysis of 372 GCLM patients (2010-2018).
  • Development and validation cohorts (2:1 ratio).
  • Cox regression, ROC analysis, calibration, and decision curve analysis used to build and assess the nomogram.

Main Results:

  • Five independent risk factors identified: albumin, primary tumor size, extrahepatic metastases, surgery, and chemotherapy.
Keywords:
Gastric cancerLiver metastasesNomogramPrognostic model

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  • Nomogram demonstrated strong predictive accuracy (AUCs ranging from 0.753 to 0.923 across cohorts and time points).
  • Excellent calibration and substantial clinical net benefit observed.

    • Conclusions:

    • Significant prognostic factors for GCLM were identified.
    • A reliable nomogram for predicting GCLM patient outcomes was developed.
    • The nomogram shows potential for clinical application in patient management.
    Survival analysis