Development and validation of a model to predict survival in colorectal cancer using a gradient-boosted machine.

Journal: Gut
Published Date: May 1, 2021

Abstract

OBJECTIVE: The success of treatment planning relies critically on our ability to predict the potential benefit of a therapy. In colorectal cancer (CRC), several nomograms are available to predict different outcomes based on the use of tumour specific features. Our objective is to provide an accurate and explainable prediction of the risk to die within 10 years after CRC diagnosis, by incorporating the tumour features and the patient medical and demographic information.

Authors

  • Jean-Emmanuel Bibault
    Radiation Oncology Department, Georges Pompidou European Hospital, Assistance Publique - Hôpitaux de Paris, Paris Descartes University, Paris Sorbonne Cité, Paris, France; INSERM UMR 1138 Team 22: Information Sciences to support Personalized Medicine, Paris Descartes University, Sorbonne Paris Cité, Paris, France. Electronic address: jean-emmanuel.bibault@aphp.fr.
  • Daniel T Chang
    Department of Radiation Oncology, School of Medicine, Stanford University, Stanford, California 94305.
  • Lei Xing
    Department of Radiation Oncology, Stanford University, CA, USA.

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