Drug Safety

, Volume 37, Issue 2, pp 99–108

Signal Detection of Potentially Drug-Induced Acute Liver Injury in Children Using a Multi-Country Healthcare Database Network

  • Carmen Ferrajolo
  • Preciosa M. Coloma
  • Katia M. C. Verhamme
  • Martijn J. Schuemie
  • Sandra de Bie
  • Rosa Gini
  • Ron Herings
  • Giampiero Mazzaglia
  • Gino Picelli
  • Carlo Giaquinto
  • Lorenza Scotti
  • Paul Avillach
  • Lars Pedersen
  • Francesco Rossi
  • Annalisa Capuano
  • Johan van der Lei
  • Gianluca Trifiró
  • Miriam C. J. M. Sturkenboom
  • EU-ADR consortium
Original Research Article

DOI: 10.1007/s40264-013-0132-9

Cite this article as:
Ferrajolo, C., Coloma, P.M., Verhamme, K.M.C. et al. Drug Saf (2014) 37: 99. doi:10.1007/s40264-013-0132-9

Abstract

Background

Data mining in spontaneous reporting databases has shown that drug-induced liver injury is infrequently reported in children.

Objectives

Our objectives were to (i) identify drugs potentially associated with acute liver injury (ALI) in children and adolescents using electronic healthcare record (EHR) data; and (ii) to evaluate the significance and novelty of these associations.

Methods

We identified potential cases of ALI during exposure to any prescribed/dispensed drug for individuals <18 years old from the EU-ADR network, which includes seven databases from three countries, covering the years 1996–2010. Several new methods for signal detection were applied to identify all statistically significant associations between drugs and ALI. A drug was considered statistically significantly associated with ALI, using all other time as a reference category, if the 95 % CI lower band of the relative risk was >1 and in the presence of at least three exposed cases of ALI. Potentially new signals were distinguished from already known associations concerning ALI (whether in adults and/or in the paediatric population) through manual review of published literature and drug product labels.

Results

The study population comprised 4,838,146 individuals aged <18 years, who contributed an overall 25,575,132 person-years of follow-up. Within this population, we identified 1,015 potential cases of ALI. Overall, 20 positive drug–ALI associations were detected. The associations between ALI and domperidone, flunisolide and human insulin were considered as potentially new signals. Citalopram and cetirizine have been previously described as hepatotoxic in adults but not in children, while all remaining associations were already known in both adults and children.

Conclusions

Data mining of multiple EHR databases for signal detection confirmed known associations between ALI and several drugs, and identified some potentially new signals in children that require further investigation through formal epidemiologic studies. This study shows that EHRs may complement traditional spontaneous reporting systems for signal detection and strengthening.

Supplementary material

40264_2013_132_MOESM1_ESM.docx (17 kb)
Supplementary material 1 (DOCX 17 kb)

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Carmen Ferrajolo
    • 1
    • 2
  • Preciosa M. Coloma
    • 1
  • Katia M. C. Verhamme
    • 1
  • Martijn J. Schuemie
    • 1
  • Sandra de Bie
    • 1
  • Rosa Gini
    • 3
  • Ron Herings
    • 4
  • Giampiero Mazzaglia
    • 5
  • Gino Picelli
    • 6
  • Carlo Giaquinto
    • 7
  • Lorenza Scotti
    • 8
  • Paul Avillach
    • 9
  • Lars Pedersen
    • 10
  • Francesco Rossi
    • 2
  • Annalisa Capuano
    • 2
  • Johan van der Lei
    • 1
  • Gianluca Trifiró
    • 1
    • 11
  • Miriam C. J. M. Sturkenboom
    • 1
    • 12
  • EU-ADR consortium
  1. 1.Department of Medical InformaticsErasmus University Medical CenterRotterdamThe Netherlands
  2. 2.Pharmacology Section, Department of Experimental Medicine, Campania Regional Center of Pharmacovigilance and PharmacoepidemiologySecond University of NaplesNaplesItaly
  3. 3.Regional Health Agency of TuscanyFlorenceItaly
  4. 4.PHARMO InstituteUtrechtThe Netherlands
  5. 5.Italian College of General PractitionersFlorenceItaly
  6. 6.Pedianet-Società Servizi Telematici SRLPaduaItaly
  7. 7.Department of PaediatricsUniversity Hospital of PaduaPaduaItaly
  8. 8.Department of Statistics and Quantitative MethodsUniversity of Milano-BicoccaMilanItaly
  9. 9.LESIM, ISPEDUniversity of Bordeaux 2BordeauxFrance
  10. 10.Department of Clinical EpidemiologyAarhus University HospitalAarhusDenmark
  11. 11.Department of Clinical and Experimental MedicineUniversity of MessinaMessinaItaly
  12. 12.EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands