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

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

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. Patients and Methods: A retrospective...

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Bibliographic Details
Main Authors: Huili Zhao, Shenao Zhang, Lang Chen, Xin Liu, Aihong Cao, Peng Du
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Translational Oncology
Subjects:
Decision tree
Therapeutic efficacy
Relapsed primary central nervous system lymphoma
Stereotactic radiosurgery
Salvage therapy
Online Access:http://www.sciencedirect.com/science/article/pii/S193652332500213X
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