Interpretable machine learning models based on body composition and inflammatory nutritional index (BCINI) to predict early postoperative recurrence of colorectal cancer: Multi-center study.

Journal: Computer methods and programs in biomedicine
Published Date: May 22, 2025

Abstract

BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) ranks among the most prevalent cancers worldwide, with early postoperative recurrence remaining a major cause of mortality. Body composition and inflammatory-nutritional indices (BCINI) have demonstrated potential in reflecting patients' physiological states; however, their association with early recurrence (ER) after CRC resection remains unclear. This study aimed to establish and validate interpretable machine learning (ML) models based on BCINI to predict ER after CRC resection.

Authors

  • Yongjie Zhou
    Department of Radiology, Jiangxi Cancer Hospital, Nanchang, China; The Second Affiliated Hospital of Nanchang Medical College, Nanchang, China; Jiangxi Clinical Research Center for Cancer, Nanchang, China.
  • Jinhong Zhao
    Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
  • Fei Zou
    Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Yongming Tan
    Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
  • Wei Zeng
    State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
  • Jiahui Jiang
    Hangzhou First People's Hospital, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
  • Jiale Hu
    Department of Radiology, Jiangxi Cancer Hospital & Institute, Jiangxi Clinical Research Center for Cancer, The Second Affiliated Hospital of Nanchang Medical College, Nanchang, China.
  • Qiao Zeng
    Jingtai Technology Co. Ltd Floor 4, No. 9, Yifenghua Industrial Zone, 91 Huaning Road, Longhua District Shenzhen Guangdong Province 518109 China.
  • Lianggeng Gong
    Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China.
  • Lan Liu
    School of Statistics, University of Minnesota at Twin Cities.
  • Linhua Zhong
    Department of Radiology, Jiangxi Cancer Hospital, Nanchang, China.

Keywords

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