Novel clinical phenotypes, drug categorization, and outcome prediction in drug-induced cholestasis: Analysis of a database of 432 patients developed by literature review and machine learning support.

Journal: Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
PMID: 38574623

Abstract

BACKGROUND: Serum transaminases, alkaline phosphatase and bilirubin are common parameters used for DILI diagnosis, classification, and prognosis. However, the relevance of clinical examination, histopathology and drug chemical properties have not been fully investigated. As cholestasis is a frequent and complex DILI manifestation, our goal was to investigate the relevance of clinical features and drug properties to stratify drug-induced cholestasis (DIC) patients, and to develop a prognosis model to identify patients at risk and high-concern drugs.

Authors

  • Marta Moreno-Torres
    Joint Research Unit in Experimental Hepatology, Dep. Biochemistry and Molecular Biology, University of Valencia, Health Research Institute Hospital La Fe & CIBER of Hepatic and Digestive Diseases, Spain. Electronic address: marta.moreno.torres@uv.es.
  • Ernesto López-Pascual
    Joint Research Unit in Experimental Hepatology, Dep. Biochemistry and Molecular Biology, University of Valencia, Health Research Institute Hospital La Fe & CIBER of Hepatic and Digestive Diseases, Spain.
  • Anna Rapisarda
    Joint Research Unit in Experimental Hepatology, Dep. Biochemistry and Molecular Biology, University of Valencia, Health Research Institute Hospital La Fe & CIBER of Hepatic and Digestive Diseases, Spain.
  • Guillermo Quintás
    Health and Biomedicine, LEITAT Technological Center, Barcelona, Spain.
  • Annika Drees
    Entity of In Vitro Toxicology and Dermato-Cosmetology, Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Belgium.
  • Inger-Lise Steffensen
    Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway.
  • Thomas Luechtefeld
    Johns Hopkins University, Bloomberg School of Public Health, Center for Alternatives to Animal Testing, Baltimore, MD, USA.
  • Eva Serrano-Candelas
    ProtoQSAR SL, Centro Europeo de Empresas Innovadoras (CEEI), Parque Tecnológico de Valencia, Valencia, Spain.
  • Marina Garcia de Lomana
    Bayer AG, Machine Learning Research, Research & Development, Pharmaceuticals, Berlin 13353, Germany.
  • Domenico Gadaleta
    Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via Giuseppe La Masa 19, 20156 Milan, Italy. Electronic address: domenico.gadaleta@marionegri.it.
  • Hubert Dirven
    Norwegian Institute of Public Health Oslo Norway.
  • Mathieu Vinken
    Department of In Vitro Toxicology and Dermato-Cosmetology, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
  • Ramiro Jover
    Department of Biochemistry and Molecular Biology, University of Valencia-Spain, and Experimental Hepatology Unit, IIS Hospital La Fe of Valencia, CIBERehd, Spain.

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