Development of a prognostic model related to homologous recombination deficiency in glioma based on multiple machine learning.

Journal: Frontiers in immunology
PMID: 39434883

Abstract

BACKGROUND: Despite advances in neuro-oncology, treatments of glioma and tools for predicting the outcome of patients remain limited. The objective of this research is to construct a prognostic model for glioma using the Homologous Recombination Deficiency (HRD) score and validate its predictive capability for glioma.

Authors

  • Zhenyu Gong
  • Dairan Zhou
    Department of Neurosurgery, Changzheng Hospital, Naval Medical University, Shanghai, China.
  • Haotian Shen
  • Chao Ma
  • Dejun Wu
    Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
  • Lijun Hou
    Department of Neurosurgery, Changzheng Hospital, Naval Medical University, Shanghai, China.
  • Hongxiang Wang
    Department of Neurosurgery, Changhai Hospital, Naval Medical University, Shanghai, China.
  • Tao Xu
    Department of Urology, Peking University People's Hospital, Beijing, China.

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