Development and External Validation of a Machine Learning Model for Prediction of Lymph Node Metastasis in Patients with Prostate Cancer.

Journal: European urology oncology
Published Date:

Abstract

BACKGROUND: Pelvic lymph node dissection (PLND) is the gold standard for diagnosis of lymph node involvement (LNI) in patients with prostate cancer. The Roach formula, Memorial Sloan Kettering Cancer Center (MSKCC) calculator, and Briganti 2012 nomogram are elegant and simple traditional tools used to estimate the risk of LNI and select patients for PLND.

Authors

  • Ali Sabbagh
    Department of Radiation Oncology, University of California-San Francisco, San Francisco, CA, USA.
  • Samuel L Washington
    University of California, San Francisco, San Francisco, CA.
  • Derya Tilki
    Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany; Department of Urology, University Hospital Hamburg-Eppendorf, Hamburg, Germany. Electronic address: d.tilki@uke.de.
  • Julian C Hong
    All Authors: Duke University, Durham, NC.
  • Jean Feng
    Department of Biostatistics, University of Washington, Seattle, WA.
  • Gilmer Valdes
    Department of Radiation Oncology, University of California, San Francisco, California.
  • Ming-Hui Chen
  • Jing Wu
    School of Pharmaceutical Science, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Hartwig Huland
    Sami-Ramzi Leyh-Bannurah, Dirk Pehrke, Hartwig Huland, Markus Graefen, and Lars Budäus, Prostate Cancer Center Hamburg-Eppendorf; Sami-Ramzi Leyh-Bannurah, Margit Fisch, and Guido Sauter, University Medical Center Hamburg-Eppendorf, Hamburg; Ulrich Wolffgang, University of Muenster, Muenster, Germany; and Zhe Tian and Pierre I. Karakiewicz, University of Montreal Health Center, Montreal, Canada.
  • Markus Graefen
    Martini-Klinik Prostate Cancer Center, Hamburg, Germany.
  • Thomas Wiegel
    Department of Radio Oncology, University Hospital Ulm, Ulm, Germany.
  • Dirk Böhmer
    Department of Radiation Oncology, Charité University Hospital, Berlin, Germany.
  • Janet E Cowan
    University of California, San Francisco, San Francisco, CA.
  • Matthew Cooperberg
    Department of Urology, University of California-San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California-San Francisco, San Francisco, CA, USA.
  • Felix Y Feng
    Department of Radiation Oncology, University of California, San Francisco, San Francisco.
  • Mack Roach
    Department of Radiation Oncology, University of California at San Francisco, San Francisco, California; Department of Urology, University of California at San Francisco, San Francisco, California.
  • Bruce J Trock
    Division of Epidemiology, Brady Urological Institute, Johns Hopkins Medical Institution, Baltimore, MD, USA.
  • Alan W Partin
    Department of Urology, Brady Urological Institute, Johns Hopkins Medical Institution, Baltimore, MD, USA.
  • Anthony V D'Amico
    Department of Radiation Oncology, Brigham and Women's Hospital and Dana Farber Cancer Institute, Boston, MA, USA.
  • Peter R Carroll
    University of California, San Francisco, San Francisco, CA.
  • Osama Mohamad
    Department of Radiation Oncology, University of California, San Francisco, San Francisco.