Development and evaluation of a multivariable prediction model for overall survival in advanced stage pulmonary carcinoid using machine learning.

Journal: European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Published Date: Feb 25, 2025

Abstract

BACKGROUND: Evidence is limited on whether patients with advanced pulmonary carcinoid (APC) benefit from comprehensive pulmonary resection (CPR), chemotherapy, or radiotherapy. Existing prognostic models for APC are limited and do not guide treatment selection. This study aims to develop and evaluate a multivariable machine learning model to predict overall survival in APC patients and provide a web-based prognostic tool.

Authors

  • Huiping Dai
    Department of Proctology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, Zhejiang, People's Republic of China. dhp20221316@hznu.edu.cn.
  • Guang Li
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
  • Cheng Zhang
    College of Forestry, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China.
  • Qi Huo
    Department of Oncology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, Zhejiang, People's Republic of China.
  • Tingting Tang
    Department of Internal Medicine, Jinping District People's Hospital of Shantou, Shantou, China.
  • Fei Ding
    Information Processing and Communication Technology Lab, Shanghai Institute of Satellite Engineering, Shanghai, China.
  • Jianjun Wang
    School of Fine Arts and Design, Leshan Normal University, Leshan, Sichuan, China.
  • Guangliang Duan
    Department of Oncology, The Affiliated Hospital of Hangzhou Normal University, Zhengzhou, Zhejiang, People's Republic of China. Electronic address: dgl20171926@hznu.edu.cn.

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