External Validation of the Bone Metastases Ensemble Trees for Survival (BMETS) Machine Learning Model to Predict Survival in Patients With Symptomatic Bone Metastases.

Journal: JCO clinical cancer informatics
PMID: 33760638

Abstract

PURPOSE: The Bone Metastases Ensemble Trees for Survival (BMETS) model uses a machine learning algorithm to estimate survival time following consultation for palliative radiation therapy for symptomatic bone metastases (SBM). BMETS was developed at a tertiary-care, academic medical center, but its validity and stability when applied to external data sets are unknown.

Authors

  • Christen R Elledge
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD.
  • Anna W LaVigne
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Jacob Fiksel
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
  • Jean L Wright
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD.
  • Todd McNutt
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Lawrence R Kleinberg
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Chen Hu
    Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland.
  • Thomas J Smith
    Biomolecular Research Centre, Sheffield Hallam University, City Campus, Sheffield, S1 1WB, UK.
  • Scott Zeger
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
  • Theodore L DeWeese
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD.
  • Sara R Alcorn
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD. Electronic address: salcorn2@jhmi.edu.

Keywords

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