[Exploration of the Predictive Value of Peripheral Blood-related Indicators for EGFR 
Mutations and Prognosis in Non-small Cell Lung Cancer Using Machine Learning].

Journal: Zhongguo fei ai za zhi = Chinese journal of lung cancer
PMID: 40114487

Abstract

BACKGROUND: Epidermal growth factor receptor (EGFR) sensitive mutation is one of the effective targets of targeted therapy for non-small cell lung cancer (NSCLC). However, due to the difficulty of obtaining some primary tissues and the economic factors in some underdeveloped areas, some patients cannot undergo traditional genetic testing. The aim of this study is to establish a machine learning (ML) model using non-invasive peripheral blood markers to explore the biomarkers closely related to EGFR mutation status in NSCLC and evaluate their potential prognostic value.

Authors

  • Shulei Fu
    The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research,
Nanjing 210009, China.
  • Shaodi Wen
    Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China.
  • Jiaqiang Zhang
    Inner Mongolia University, Hohhot 010000, China.
  • Xiaoyue Du
    The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research,
Nanjing 210009, China.
  • Ru Li
    Inner Mongolia University, Hohhot 010000, China.
  • Bo Shen
    School of Information Science and Technology, Donghua University, Shanghai 200051, China. Electronic address: Bo.Shen@dhu.edu.cn.

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