Signal detection of potentially drug-induced acute liver injury in children using a multi-country healthcare database network.
BACKGROUND
Data mining in spontaneous reporting databases has shown that drug-induced liver injury is infrequently reported in children.


OBJECTIVE
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.
Department of Medical Informatics, Erasmus University Medical Center, Dr. Molewaterplein 50, 3015 GE, Rotterdam, The Netherlands, c.ferrajolo@erasmusmc.nl.
Carmen
C
Ferrajolo
Preciosa M
PM
Coloma
Katia M C
KM
Verhamme
Martijn J
MJ
Schuemie
Sandra
S
de Bie
Rosa
R
Gini
Ron
R
Herings
Giampiero
G
Mazzaglia
Gino
G
Picelli
Carlo
C
Giaquinto
Lorenza
L
Scotti
Paul
P
Avillach
Lars
L
Pedersen
Francesco
F
Rossi
Annalisa
A
Capuano
Johan
J
van der Lei
Gianluca
G
Trifiró
Miriam C J M
MC
Sturkenboom
D000293:Adolescent; D016907:Adverse Drug Reaction Reporting Systems / Q000458:organization & administration / Q000706:statistics & numerical data; D056486:Chemical and Drug Induced Liver Injury / Q000453:epidemiology* / Q000209:etiology; D002648:Child; D002669:Child Welfare; D002675:Child, Preschool; D057225:Data Mining; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology* / Q000209:etiology; D057286:Electronic Health Records; D005062:European Union; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007391:International Cooperation; D017114:Liver Failure, Acute / Q000453:epidemiology* / Q000209:etiology