Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care.

Journal: JCO clinical cancer informatics
PMID: 40184559

Abstract

PURPOSE: The use of real-world data (RWD) in oncology is becoming increasingly important for clinical decision making and tailoring treatment. Despite the significant success of targeted therapy and immunotherapy in advanced melanoma, substantial variability in clinical responses to these treatments emphasizes the need for personalized approaches to therapy.

Authors

  • Richard M Brohet
    Diabetes Research Center and Department of Epidemiology and Statistics, Isala Hospital, Zwolle, The Netherlands.
  • Elianne C S de Boer
    Department of Oncology Center, Isala, Zwolle, the Netherlands.
  • Joram M Mossink
    Division Data Science, Department of Innovation and Science, Isala, Zwolle, the Netherlands.
  • Joni J N van der Eerden
    Division Data Science, Department of Innovation and Science, Isala, Zwolle, the Netherlands.
  • Alexander Oostmeyer
    Division Data Science, Department of Innovation and Science, Isala, Zwolle, the Netherlands.
  • Luuk H W Idzerda
    Division Data Science, Department of Innovation and Science, Isala, Zwolle, the Netherlands.
  • Jan Gerard Maring
    Department of Clinical Pharmacy, Isala, Zwolle, the Netherlands.
  • Gabriel M R M Paardekooper
    Department of Radiotherapy, Isala, Zwolle, the Netherlands.
  • Michel Beld
    Department of Business Intelligence, Isala, Zwolle, the Netherlands.
  • Fiona Lijffijt
    Department of Medical Ethics & Legal Affairs, Isala, Zwolle, the Netherlands.
  • Joep Dille
    Department of Innovation and Science, Isala, Zwolle, the Netherlands.
  • Jan Willem B de Groot
    Department of Oncology Center, Isala, Zwolle, the Netherlands.

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