Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.

Journal: Clinical orthopaedics and related research
PMID: 38470976

Abstract

BACKGROUND: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling approaches such as traditional survivorship estimators (such as Kaplan-Meier) or competing risk estimators. Recent advances in machine learning survival analysis might improve decision support tools in this setting. Therefore, this study aimed to assess the performance of machine learning compared with that of conventional modeling to predict revision after arthroplasty.

Authors

  • Jacobien H F Oosterhoff
    Orthopedic Oncology Service, Massachusetts General Hospital, Harvard Medical School, Boston, USA;
  • Anne A H de Hond
    Clinical AI Implementation and Research Lab, Leiden University Medical Center, Leiden, The Netherlands.
  • Rinne M Peters
    Department of Orthopaedic Surgery, Medical Center Leeuwarden, Leeuwarden, the Netherlands.
  • Liza N van Steenbergen
    Dutch Arthroplasty Register (LROI), 's-Hertogenbosch, the Netherlands.
  • Juliette C Sorel
    Department of Orthopaedic Surgery, Leiden University Medical Centre, Leiden, the Netherlands.
  • Wierd P Zijlstra
    Department of Orthopaedic Surgery, Medical Center Leeuwarden, Leeuwarden, the Netherlands.
  • Rudolf W Poolman
    Department of Orthopaedic Surgery, Leiden University Medical Centre, Leiden, the Netherlands.
  • David Ring
  • Paul C Jutte
    Department of Orthopaedic Surgery, Groningen University Medical Centre, Groningen, the Netherlands.
  • Gino M M J Kerkhoffs
  • Hein Putter
    Department of Biomedical Data Sciences, Section Medical Statistics, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA Leiden, Netherlands.
  • Ewout W Steyerberg
    Department of Biomedical Data Sciences, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA The Netherlands.
  • Job N Doornberg

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