Rapid identification of tumor patients with PG-SGA ≥ 4 based on machine learning: a prospective study.

Journal: BMC cancer
Published Date:

Abstract

BACKGROUND: Malnutrition is common in cancer patients and worsens treatment and prognosis. The Patient-Generated Subjective Global Assessment (PG-SGA) is the best tool to evaluate malnutrition, but it is complicated has limited its routine clinical use.

Authors

  • Gui Qian
    School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
  • Huang Jiaxin
    Department of Comprehensive Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Cong Minghua
    Department of Comprehensive Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Liu Beijia
    School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
  • Li Yinfeng
    Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital &Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
  • Huang Guiyu
    Department of Chest Radiotherapy, Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
  • Yang Mingxue
    Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital &Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
  • Tang Xiaoli
    Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital &Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China. 1585470513@qq.com.
  • Yan Hongyan
    Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital &Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China. 1752146434@qq.com.