Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay.

Journal: Breast cancer research and treatment
PMID: 38592541

Abstract

PURPOSE: To evaluate the Stratipath Breast tool for image-based risk profiling and compare it with an established prognostic multigene assay for risk profiling in a real-world case series of estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients categorized as intermediate risk based on classic clinicopathological variables and eligible for chemotherapy.

Authors

  • Yinxi Wang
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Wenwen Sun
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
  • Emelie Karlsson
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
  • Sandy Kang Lövgren
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Balazs Acs
    Department of Oncology/Pathology, Karolinska Institutet, Stockholm, Sweden; Theme Cancer, Karolinska University Hospital, Stockholm, Sweden.
  • Mattias Rantalainen
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Stephanie Robertson
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden; Department of Clinical Pathology and Cytology, Karolinska University Laboratory, Stockholm, Sweden.
  • Johan Hartman
    Department of Oncology/Pathology, Karolinska Institutet, Stockholm, Sweden; Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.

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