Clinical decision support algorithm based on machine learning to assess the clinical response to anti-programmed death-1 therapy in patients with non-small-cell lung cancer.

Journal: European journal of cancer (Oxford, England : 1990)
Published Date: Jun 26, 2021

Abstract

OBJECTIVE: Anti-programmed death (PD)-1 therapy confers sustainable clinical benefits for patients with non-small-cell lung cancer (NSCLC), but only some patients respond to the treatment. Various clinical characteristics, including the PD-ligand 1 (PD-L1) level, are related to the anti-PD-1 response; however, none of these can independently serve as predictive biomarkers. Herein, we established a machine learning (ML)-based clinical decision support algorithm to predict the anti-PD-1 response by comprehensively combining the clinical information.

Authors

  • Beung-Chul Ahn
    Division of Medical Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Jea-Woo So
    TheragenBio, Seongnam, Republic of Korea.
  • Chun-Bong Synn
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea; Brain Korea 21 Plus Project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Tae Hyung Kim
    TheragenBio, Seongnam, Republic of Korea.
  • Jae Hwan Kim
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Yeongseon Byeon
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Young Seob Kim
    Department of Research Support, Yonsei Biomedical Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Seong Gu Heo
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • San-Duk Yang
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Mi Ran Yun
    JEUK Institute for Cancer Research, JEUK Co., Ltd., Gumi-City, Republic of Korea.
  • Sangbin Lim
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Su-Jin Choi
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea; Brain Korea 21 Plus Project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Wongeun Lee
    JEUK Institute for Cancer Research, JEUK Co., Ltd., Gumi-City, Republic of Korea.
  • Dong Kwon Kim
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea; Brain Korea 21 Plus Project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Eun Ji Lee
    Department of Pathology, Green Cross Laboratories, Yongin, Gyeonggi, South Korea.
  • Seul Lee
    Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea; Brain Korea 21 Plus Project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Doo-Jae Lee
    Wide River Institute of Immunology (WRII) Seoul National University, Hongcheon-gun, Gangwon-do 250-812, Republic of Korea.
  • Chang Gon Kim
    Division of Medical Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Sun Min Lim
    Division of Medical Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Min Hee Hong
    Division of Medical Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Byoung Chul Cho
    Division of Medical Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Kyoung-Ho Pyo
    Division of Medical Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea; Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea. Electronic address: pkhpsh@yuhs.ac.
  • Hye Ryun Kim
    Division of Medical Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea. Electronic address: nobelg@yuhs.ac.

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