Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study.

Journal: Breast (Edinburgh, Scotland)
Published Date: May 7, 2025

Abstract

PURPOSE: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. This study aims to enhance pre-selection of patients for testing using machine learning.

Authors

  • Una Kjällquist
    Department of Oncology/Pathology, Karolinska Institutet, Stockholm, Sweden; Theme Cancer, Karolinska University Hospital, Stockholm, Sweden. Electronic address: una.kjallquist@ki.se.
  • Nikos Tsiknakis
    Computational BioMedicine Laboratory, Foundation for Research and Technology Hellas, Greece; Department of Oncology, Pathology, Karolinska Institute, Sweden.
  • Balazs Acs
    Department of Oncology/Pathology, Karolinska Institutet, Stockholm, Sweden; Theme Cancer, Karolinska University Hospital, Stockholm, Sweden.
  • Sara Margolin
    Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden; Department of Oncology, Södersjukhuset, Stockholm, Sweden.
  • Luisa Edman Kessler
    Breast Center, Capio St:Göran's Hospital, Stockholm, Sweden.
  • Scarlett Levy
    Breast Center, Capio St:Göran's Hospital, Stockholm, Sweden.
  • Maria Ekholm
    Department of Oncology, Ryhov County Hospital, Jönköping, Sweden; Department of Biomedical and Clinical Sciences, Division of Oncology, Linköping University, Linköping, Sweden.
  • Christine Lundgren
    Department of Oncology, Ryhov County Hospital, Jönköping, Sweden; Department of Biomedical and Clinical Sciences, Division of Oncology, Linköping University, Linköping, Sweden.
  • Erik Olsson
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
  • Henrik Lindman
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
  • Antonios Valachis
    Department of Oncology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
  • Johan Hartman
    Department of Oncology/Pathology, Karolinska Institutet, Stockholm, Sweden; Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
  • Theodoros Foukakis
    Department of Oncology/Pathology, Karolinska Institutet, Stockholm, Sweden; Theme Cancer, Karolinska University Hospital, Stockholm, Sweden.
  • Alexios Matikas
    Department of Oncology/Pathology, Karolinska Institutet, Stockholm, Sweden; Theme Cancer, Karolinska University Hospital, Stockholm, Sweden. Electronic address: alexios.matikas@ki.se.

Keywords

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