Real-World and Clinical Trial Validation of a Deep Learning Radiomic Biomarker for PD-(L)1 Immune Checkpoint Inhibitor Response in Advanced Non-Small Cell Lung Cancer.

Journal: JCO clinical cancer informatics
PMID: 39671539

Abstract

PURPOSE: This study developed and validated a novel deep learning radiomic biomarker to estimate response to immune checkpoint inhibitor (ICI) therapy in advanced non-small cell lung cancer (NSCLC) using real-world data (RWD) and clinical trial data.

Authors

  • Chiharu Sako
    Center for Biomedical Image Computing and Analytics.
  • Chong Duan
    Early Clinical Development, Pfizer Incorporated, Cambridge, Massachusetts.
  • Kevin Maresca
    Pfizer, Cambridge, MA.
  • Sean Kent
    Pfizer, Cambridge, MA.
  • Taly Gilat Schmidt
    Onc.AI, San Carlos, CA.
  • Hugo J W L Aerts
    Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.
  • Ravi B Parikh
    Division of Hematology and Oncology, Perelman School of Medicine, University of Philadelphia, Philadelphia, Pennsylvania.
  • George R Simon
    Moffitt Cancer Center, Tampa, FL.
  • Petr Jordan
    Varian Medical Systems, Inc., 3100 Hansen Way, Palo Alto, CA 94304, USA.

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