Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations.

Journal: British journal of cancer
Published Date: Jun 22, 2020

Abstract

BACKGROUND: The clinical utility of machine-learning (ML) algorithms for breast cancer risk prediction and screening practices is unknown. We compared classification of lifetime breast cancer risk based on ML and the BOADICEA model. We explored the differences in risk classification and their clinical impact on screening practices.

Authors

  • Chang Ming
    Nursing Science, Faculty of Medicine, University of Basel, Bernoullistrasse 28, Room 118, 4056, Basel, Switzerland. chang.ming@unibas.ch.
  • Valeria Viassolo
    Oncogenetics and Cancer Prevention, Geneva University Hospitals, Geneva, Switzerland.
  • Nicole Probst-Hensch
    Swiss Tropical and Public Health Institute Basel, Department of Epidemiology and Public Health, University of Basel, Basel, Switzerland.
  • Ivo D Dinov
    Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA; Statistics Online Computational Resource, Department of Health Behavior and Biological, University of Michigan, Ann Arbor, MI, USA.
  • Pierre O Chappuis
    Oncogenetics and Cancer Prevention, Geneva University Hospitals, Geneva, Switzerland.
  • Maria C Katapodi
    Nursing Science, Faculty of Medicine, University of Basel, Bernoullistrasse 28, Room 118, 4056, Basel, Switzerland.

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