Robustness of steroidomics-based machine learning for diagnosis of primary aldosteronism: a laboratory medicine perspective.

Journal: Clinical chemistry and laboratory medicine
Published Date: Jul 25, 2025

Abstract

OBJECTIVES: Use of machine learning (ML) in diagnostics offers promise to optimise interpretation of laboratory data and guide clinical decision-making. For this, ML-based outputs should provide robustly reproducible results at least as good as the underlying laboratory data. The objective of this study was to assess robustness of ML-based steroid-probability-scores for diagnosis of primary aldosteronism (PA).

Authors

  • Graeme Eisenhofer
    Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Medical Faculty Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Mirko Peitzsch
    Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Medical Faculty Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Kevin Mantik
    New South Wales Health Pathology, Department of Chemical Pathology, Prince of Wales Hospital, Sydney, New South Wales, Australia.
  • Manuel Schulze
    Center for Interdisciplinary Digital Sciences, Department of Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany.
  • Georgiana Constantinescu
    Department of Medicine III, Technische Universität Dresden, Dresden, Germany.
  • Zhong Lu
    Monash Health Pathology and Department of Medicine, Monash University, Victoria, Australia.
  • Hanna Remde
    Department of Internal Medicine I, Division of Endocrinology and Diabetes, University Hospital, University of Würzburg, Würzburg, Germany.
  • Carmina T Fuss
    Department of Internal Medicine I, Division of Endocrinology and Diabetes, University Hospital, University of Würzburg, Würzburg, Germany.
  • Tracy Ann Williams
    Division of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Turin, Italy.
  • Sven Gruber
    Department of Endocrinology, Diabetology and Clinical Nutrition, University Hospital and University of Zurich, Switzerland (S.G., F. Beuschlein).
  • Jacques W M Lenders
    Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Andrea Horvath
    New South Wales Health Pathology, Department of Chemical Pathology, Prince of Wales Hospital, Sydney, New South Wales, Australia.
  • Christina Pamporaki
    Department of Medicine III, University Hospital Carl Gustav Carus, TU Dresden, Germany.

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