Leveraging machine-learning techniques to detect recurrences in cancer registry data: A multi-registry validation study using German lung cancer data.

Journal: European journal of cancer (Oxford, England : 1990)
Published Date: Jul 5, 2025

Abstract

BACKGROUND: Cancer recurrence and progression, once seen as markers of poor prognosis, are now considered manageable aspects of long-term care. Advances in treatment have extended survival, emphasizing the need for representative epidemiological information. Population-based cancer registries are essential in this respect. However, tracking treatment outcomes and accurately distinguishing recurrences from progressions remain challenging due to incomplete follow-up data. To address this aiming at meaningful cancer registry data analyses, we employed machine learning (ML) for precise classification, surpassing traditional clinical assumptions.

Authors

  • Henrik Kusche
    Free and Hanseatic City of Hamburg, Ministry of Science, Research, Equality and Districts, Hamburg Cancer Registry, Süderstraße 30, Hamburg 20097, Germany. Electronic address: henrik.kusche@bwfgb.hamburg.de.
  • Christopher Gundler
    University Medical Center Hamburg-Eppendorf, Institute for Applied Medical Informatics, Martinistraße 52, Hamburg 20246, Germany.
  • Ole Johanns
    Free and Hanseatic City of Hamburg, Ministry of Science, Research, Equality and Districts, Hamburg Cancer Registry, Süderstraße 30, Hamburg 20097, Germany.
  • Markus Sauerberg
    Free and Hanseatic City of Hamburg, Ministry of Science, Research, Equality and Districts, Hamburg Cancer Registry, Süderstraße 30, Hamburg 20097, Germany.
  • Thorsten Wicker
    Free and Hanseatic City of Hamburg, Ministry of Science, Research, Equality and Districts, Hamburg Cancer Registry, Süderstraße 30, Hamburg 20097, Germany.
  • Vera Heinrichs
    Free and Hanseatic City of Hamburg, Ministry of Science, Research, Equality and Districts, Hamburg Cancer Registry, Süderstraße 30, Hamburg 20097, Germany.
  • Daniel Dettmer
    Clinical Cancer Registry of Lower Saxony, Sutelstraße 2, Hannover 30659, Germany.
  • Nils Goeken
    Clinical Cancer Registry of Lower Saxony, Sutelstraße 2, Hannover 30659, Germany.
  • Manuela Langholz
    Bremen Cancer Registry, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Achterstraße 30, Bremen 28359, Germany.
  • Sabine Luttmann
    Bremen Cancer Registry, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Achterstraße 30, Bremen 28359, Germany.
  • Peter Mazuch
    Free and Hanseatic City of Hamburg, Ministry of Science, Research, Equality and Districts, Hamburg Cancer Registry, Süderstraße 30, Hamburg 20097, Germany.
  • Ron Pritzkuleit
    Institute for Cancer Epidemiology, University of Lübeck, Cancer Registry Schleswig-Holstein, Ratzeburger Allee 160, Lübeck 23562, Germany.
  • Natalie Rath
    Saarland Cancer Registry, Neugeländstraße 9, 66117 Saarbrücken, Germany.
  • Katharina Rausch
    Saarland Cancer Registry, Neugeländstraße 9, 66117 Saarbrücken, Germany.
  • Lisa Katharina Sha
    Hessian Cancer Registry, Hessian Office of Health and Care, Frankfurt am Main 60439, Germany.
  • Alexander Sieber
    Hessian Cancer Registry, Hessian Office of Health and Care, Frankfurt am Main 60439, Germany.
  • Alexander Katalinic
    Institute for Cancer Epidemiology, University of Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany; Institute for Social Medicine and Epidemiology, University of Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany.
  • Alice Nennecke
    Free and Hanseatic City of Hamburg, Ministry of Science, Research, Equality and Districts, Hamburg Cancer Registry, Süderstraße 30, Hamburg 20097, Germany.

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