Machine Learning and Mechanistic Modeling for Prediction of Metastatic Relapse in Early-Stage Breast Cancer.

Journal: JCO clinical cancer informatics
Published Date: Mar 1, 2020

Abstract

PURPOSE: For patients with early-stage breast cancer, predicting the risk of metastatic relapse is of crucial importance. Existing predictive models rely on agnostic survival analysis statistical tools (eg, Cox regression). Here we define and evaluate the predictive ability of a mechanistic model for time to distant metastatic relapse.

Authors

  • Chiara Nicolò
    Mathematical Modeling for Oncology Team, Inria Bordeaux Sud-Ouest, Talence, France.
  • Cynthia Périer
    Mathematical Modeling for Oncology Team, Inria Bordeaux Sud-Ouest, Talence, France.
  • Melanie Prague
    Statistics in Systems Biology and Translational Medicine Team, Inria Bordeaux Sud-Ouest, University of Bordeaux, Bordeaux, France.
  • Carine Bellera
    INSERM U1219, Bordeaux Public Health, University of Bordeaux, Bordeaux, France.
  • Gaëtan MacGrogan
    Department of Biopathology, Institut Bergonié, Regional Comprehensive Cancer Centre, Bordeaux, France.
  • Olivier Saut
    INRIA Bordeaux Sud-Ouest, France.
  • Sébastien Benzekry
    Mathematical Modeling for Oncology Team, Inria Bordeaux Sud-Ouest, Talence, France.

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