Construction and validation of a prognostic nomogram model integrating machine learning-pathomics and clinical features in IDH-wildtype glioblastoma.

Journal: Journal of translational medicine
Published Date:

Abstract

BACKGROUND: Novel diagnostic criteria for glioblastoma (GBM) in the 2021 WHO classification emphasize the importance of integrating pathological and molecular features. Pathomics, which involves the extraction of digital pathology data, is gaining significant interest in the field of tumor research. This study aimed to construct and validate a nomogram based on machine-learning pathomics for patients with GBM.

Authors

  • Yaomin Li
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Pei Ouyang
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Zongliao Zheng
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Jiapeng Deng
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Aishun Guo
    Department of Neurosurgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, 363000, China.
  • Weiwei Wang
  • Yawei Liu
    Health Service Department of the Guard Bureau of the General Office of the Central Committee of the Communist Party of China, Xicheng, Beijing, China.
  • Yuping Peng
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Yankai Liao
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Xiran Wang
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Hai Wang
    School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China.
  • Zhaojun Wang
    Huaiyin Wu Jutong Institute of Traditional Chinese Medicine, Huaian 223000, China.
  • Zhitai Mo
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Jianming Weng
    Department of Pathology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, 363000, China.
  • Haiyan Xv
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Xiaoxia Zheng
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Junlu Liu
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Yajuan Wang
    College of Mathematical Medicine, Zhejiang Normal University, Jinhua 321004, China.
  • Yongfu Cao
    Neurosurgery, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou Dadao Bei Street 1838#, Guangzhou, 510799, Guangdong, China.
  • GuangLong Huang
    Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Xian Zhang
    The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, China.
  • Songtao Qi
    Department of Neurosurgery, Institute of Brain Disease, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China. qisongtaonfyy@126.com.