Machine Learning-Based Prediction of 1-Year Survival Using Subjective and Objective Parameters in Patients With Cancer.

Journal: JCO clinical cancer informatics
PMID: 39197123

Abstract

PURPOSE: Palliative care is recommended for patients with cancer with a life expectancy of <12 months. Machine learning (ML) techniques can help in predicting survival outcomes among patients with cancer and may help distinguish who benefits the most from palliative care support. We aim to explore the importance of several objective and subjective self-reported variables. Subjective variables were collected through electronic psycho-oncologic and palliative care self-assessment screenings. We used these variables to predict 1-year mortality.

Authors

  • Maria Rosa Salvador Comino
    Department of Palliative Medicine, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
  • Paul Youssef
    Institute for Artificial Intelligence in Medicine (IKIM), University of Duisburg-Essen, Essen, Germany.
  • Anna Heinzelmann
    Department of Palliative Medicine, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
  • Florian Bernhardt
    Department of Palliative Care, West German Cancer Center, University Hospital Muenster, University of Muenster, Muenster, Germany.
  • Christin Seifert
    Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, 45131 Essen, Germany.
  • Mitra Tewes
    Department of Palliative Medicine, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.

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