Development and validation of machine learning nomograms for predicting survival in stage IV pancreatic cancer: A retrospective study.

Journal: World journal of gastrointestinal oncology
Published Date: May 15, 2025

Abstract

BACKGROUND: Stage IV pancreatic cancer (PC) has a poor prognosis and lacks individualized prognostic tools. Current survival prediction models are limited, and there is a need for more accurate, personalized methods. The Surveillance, Epidemiology, and End Results (SEER) database offers a valuable resource for studying large patient cohorts, yet machine learning-based nomograms for stage IV PC prognosis remain underexplored. This study hypothesizes that a machine learning-based nomogram can predict cancer-specific survival (CSS) and overall survival (OS) with high accuracy in stage IV PC patients.

Authors

  • Kun Huang
    Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA. Kun.Huang@osumc.edu.
  • Zhu Chen
    Economical Forest Cultivation and Utilization of 2011 Collaborative Innovation Center in Hunan Province, Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China.
  • Xin-Zhu Yuan
    Department of Nephrology, The Second Clinical Medical Institution of North Sichuan Medical College (Nanchong Central Hospital) and Nanchong Key Laboratory of Basic Science & Clinical Research on Chronic Kidney Disease, Nanchong 637000, Sichuan Province, China.
  • Yun-Shen He
    Department of General Surgery, Mianyang Hospital of Traditional Chinese Medicine, Mianyang 621000, Sichuan Province, China.
  • Xiang Lan
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400000, China. lanxiangkeyan@163.com.
  • Chen-You Du
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400000, China.

Keywords

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