Prognosticating salvage stereotactic radiosurgery outcomes in relapsed primary central nervous system lymphoma: A machine learning-driven decision tree analysis.

Journal: Translational oncology
Published Date:

Abstract

PURPOSE: To identify key clinical risk factors affecting therapeutic outcomes in relapsed primary central nervous system lymphoma (r-PCNSL) patients undergoing stereotactic radiosurgery salvage therapy (SRS-ST) and develop a decision tree-based predictive model.

Authors

  • Huili Zhao
    Department of Radiology, The Second Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, China; Department of Radiology, Xinyi People's Hospital, Xuzhou 221400, China.
  • Shenao Zhang
    Department of Radiology, The Second Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, China.
  • Lang Chen
    University of Wisconsin-Madison.
  • Xin Liu
    Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences, Weifang, Shandong, China.
  • Aihong Cao
    Department of Radiology, the Second Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China.
  • Peng Du
    Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.

Keywords

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