Training, Validating, and Testing Machine Learning Prediction Models for Endometrial Cancer Recurrence.

Journal: JCO precision oncology
PMID: 40324114

Abstract

PURPOSE: Endometrial cancer (EC) is the most common gynecologic cancer in the United States with rising incidence and mortality. Despite optimal treatment, 15%-20% of all patients will recur. To better select patients for adjuvant therapy, it is important to accurately predict patients at risk for recurrence. Our objective was to train, validate, and test models of EC recurrence using lasso regression and other machine learning (ML) and deep learning (DL) analytics in a large, comprehensive data set.

Authors

  • Jesus Gonzalez Bosquet
    Department of Obstetrics and Gynecology, Gynecologic Oncology, University of Iowa, Iowa City, IA.
  • Andrew Polio
    Department of Obstetrics and Gynecology, Gynecologic Oncology, University of Iowa, Iowa City, IA.
  • Erin George
    Gynecologic Oncology, Moffit Cancer Center, Tampa, FL.
  • Ahmad A Tarhini
    Departments of Cutaneous Oncology and Immunology, H. Lee Moffit Cancer Center & Research Institute, Tampa, FL.
  • Casey M Cosgrove
    Gynecologic Oncology, The Ohio State University, Columbus, OH.
  • Marilyn S Huang
    Gynecologic Oncology, University of Virginia, Charlottesville, VA.
  • Bradley Corr
    Gynecologic Oncology, University of Colorado, Aurora, CO.
  • Aliza L Leiser
    Gynecologic Oncology, Rutgers, New Brunswick, NJ.
  • Bodour Salhia
    Department of Translational Genomics Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.
  • Kathleen Darcy
    Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD.
  • Christopher M Tarney
    Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD.
  • Rob L Dood
    Gynecologic Oncology, Huntsman Cancer Institute, Salt Lake City, UT.
  • Lauren E Dockery
    Gynecologic Oncology, University of Oklahoma, Oklahoma City, OK.
  • Stephen B Edge
    Surgical Oncology, Roswell Park Comprehensive Cancer Center, Elm & Carlton Streets, Buffalo, NY.
  • Michael J Cavnar
    Surgical Oncology, University of Kentucky, UKMC-C224, Lexington KY.
  • Lisa Landrum
    Gynecologic Oncology, Indiana University, Indianapolis, IN.
  • Rob J Rounbehler
    Department of Clinical and Life Sciences, Aster Insights, Hudson, FL.
  • Michelle Churchman
    Aster Insights, Hudson, FL.
  • Vincent M Wagner
    Department of Obstetrics and Gynecology, Gynecologic Oncology, University of Iowa, Iowa City, IA.

Keywords

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