Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

Journal: International journal of radiation oncology, biology, physics
PMID: 32446952

Abstract

PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic covariates. To establish its relative clinical utility, we compared BMETS with 2 simpler Cox regression models used in this setting.

Authors

  • Sara R Alcorn
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD. Electronic address: salcorn2@jhmi.edu.
  • 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.
  • Christen R Elledge
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD.
  • Thomas J Smith
    Biomolecular Research Centre, Sheffield Hallam University, City Campus, Sheffield, S1 1WB, UK.
  • Powell Perng
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD.
  • Sarah Saleemi
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD.
  • Todd R McNutt
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland. Electronic address: tmcnutt1@jhmi.edu.
  • Theodore L DeWeese
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD.
  • Scott Zeger
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

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