Literature DB >> 30195258

The influence of drug properties and host factors on delayed onset of symptoms in drug-induced liver injury.

Andres Gonzalez-Jimenez1, Kristin McEuen2, Minjun Chen2, Ayako Suzuki3,4, Mercedes Robles-Diaz1, Inmaculada Medina-Caliz1, Fernando Bessone5, Nelia Hernandez6, Marco Arrese7, Raymundo Parana8, M Isabel Lucena1,9, Camilla Stephens1, Raúl J Andrade1.   

Abstract

BACKGROUND & AIMS: Most patients with drug-induced liver injury (DILI) manifest clinical symptoms while on therapy, while some patients manifest days or weeks after drug cessation (delayed onset). This challenges DILI causality assessment and diagnosis. Factors contributing to the delayed onset phenotype are currently unknown. We explored factors contributing to delayed onset of DILI by analysing culprit drug properties, host factors and their interactions in a large patient population from the Spanish DILI Registry.
METHODS: Clinical information from 388 patients (69 presented delayed onset) and drug properties of 43 causative drugs (45 active ingredients) were analysed. A two-tier regression-based model was used to assess host/drug interactions affecting the probability of delayed onset.
RESULTS: Antibacterial and anti-inflammatory drugs accounted for the delayed onset cases. Drug property of <50% hepatic metabolism (odds ratio [OR] 11.06, 95% confidence interval [95% CI]: 4.4-32.2, P = 0.0003), daily dose ≥1000 mg (OR: 2.77, 95% CI: 1.3-6.1, P = 0.0063) and the absence of pre-existing conditions in a patient (OR: 2.55, 95% CI: 1.3-4.9, P = 0.0043) were independently associated with delayed onset. The findings were consistent when externally validated using Latin American DILI Network cases (N = 131). Likewise, drug properties of mitochondrial liability and Pauling electronegativity were associated with delayed onset, but dependent on specific host factors such as age, sex and pre-existing cardiac diseases.
CONCLUSIONS: This study demonstrated that delayed onset, a specific DILI phenotype, is explained by complex interactions among drug properties and host factors and provided mechanistic hypotheses for future studies. These findings can help improve the diagnostic capability and causality assessment.
© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  data mining; hepatotoxicity; interactions; phenotype

Mesh:

Year:  2018        PMID: 30195258     DOI: 10.1111/liv.13952

Source DB:  PubMed          Journal:  Liver Int        ISSN: 1478-3223            Impact factor:   5.828


  4 in total

Review 1.  Strategies for Early Prediction and Timely Recognition of Drug-Induced Liver Injury: The Case of Cyclin-Dependent Kinase 4/6 Inhibitors.

Authors:  Emanuel Raschi; Fabrizio De Ponti
Journal:  Front Pharmacol       Date:  2019-10-24       Impact factor: 5.810

Review 2.  Preclinical models of idiosyncratic drug-induced liver injury (iDILI): Moving towards prediction.

Authors:  Antonio Segovia-Zafra; Daniel E Di Zeo-Sánchez; Carlos López-Gómez; Zeus Pérez-Valdés; Eduardo García-Fuentes; Raúl J Andrade; M Isabel Lucena; Marina Villanueva-Paz
Journal:  Acta Pharm Sin B       Date:  2021-11-18       Impact factor: 11.413

Review 3.  Drug-Induced Liver Injury: Highlights of the Recent Literature.

Authors:  Mark Real; Michele S Barnhill; Cory Higley; Jessica Rosenberg; James H Lewis
Journal:  Drug Saf       Date:  2019-03       Impact factor: 5.606

4.  Using an Automated Algorithm to Identify Potential Drug-Induced Liver Injury Cases in a Pharmacovigilance Database.

Authors:  Liliam Pineda Salgado; Ritu Gupta; Michael Jan; Osman Turkoglu; Alvin Estilo; Vinu George; Mirza I Rahman
Journal:  Adv Ther       Date:  2021-07-28       Impact factor: 3.845

  4 in total

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