EUROmediCAT signal detection: a systematic method for identifying potential teratogenic medication.
- Luteijn JM Wolfson Institute of Preventive Medicine, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
- Morris JK Wolfson Institute of Preventive Medicine, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. j.k.morris@qmul.ac.uk.
- Garne E Paediatric Department, Hospital Lillebaelt, Kolding, Denmark.
- Given J Centre for Maternal, Fetal and Infant Research, Institute of Nursing and Health Research, Ulster University, Newtownabbey, UK.
- de Jong-van den Berg L Department of Pharmacy, Unit of PharmacoEpidemiology and PharmacoEconomics, Groningen, The Netherlands.
- Addor MC Division of Medical Genetics, CHUV, Lausanne, Switzerland.
- Bakker M University Medical Centre of Groningen, Groningen, The Netherlands.
- Barisic I Department of Medical Genetics and Reproductive Health, Children's Hospital Zagreb, Medical School University of Zagreb, Zagreb, Croatia.
- Gatt M Department of Health Information and Research, Guardamangia, Malta.
- Klungsoyr K Medical Birth Registry of Norway, The Norwegian Institute of Public Health and Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
- Latos-Bielenska A Department of Medical Genetics, Poznan University of Medical Sciences, Poznan, Poland.
- Lelong N Center for biostatistics and epidemiology, INSERM U1153, Paris, France.
- Nelen V Provinciaal Instituut voor Hygiene (PIH), Antwerp, Belgium.
- Neville A IMER Registry (Emila Romagna Registry of Birth Defects), Center for Clinical and Epidemiological Research University of Ferrara and Azienda Ospedaliero- Universitaria di Ferrara, Ferrara, Italy.
- O'Mahony M Public Health Medicine, Health Service Executive, Cork, Ireland.
- Pierini A National Research Council (IFC-CNR), Institute of Clinical Pharmacology, Pisa, Italy.
- Tucker D Congenital Anomaly Register and Information Service for Wales, Public Health Wales, Swansea, UK.
- de Walle H Department of Genetics, EUROCAT Northern Netherlands, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
- Wiesel A Mainz Model Birth Registry, University Children's Hospital Mainz, Germany.
- Loane M Centre for Maternal, Fetal and Infant Research, Institute of Nursing and Health Research, Ulster University, Newtownabbey.
- Dolk H Centre for Maternal, Fetal and Infant Research, Institute of Nursing and Health Research, Ulster University, Newtownabbey, UK.
- 2016-06-30
Published in:
- British journal of clinical pharmacology. - 2016
adverse drug reactions
congenital anomalies
drug safety
pharmacoepidemiology
pharmacovigilance
pregnancy
Abnormalities, Drug-Induced
Adult
Adverse Drug Reaction Reporting Systems
Case-Control Studies
Congenital Abnormalities
Databases, Factual
Europe
Female
Humans
Pregnancy
Registries
Teratogens
Young Adult
English
AIMS
Information about medication safety in pregnancy is inadequate. We aimed to develop a signal detection methodology to routinely identify unusual associations between medications and congenital anomalies using data collected by 15 European congenital anomaly registries.
METHODS
EUROmediCAT database data for 14 950 malformed foetuses/babies with first trimester medication exposures in 1995-2011 were analyzed. The odds of a specific medication exposure (coded according to chemical substance or subgroup) for a specific anomaly were compared with the odds of that exposure for all other anomalies for 40 385 medication anomaly combinations in the data. Simes multiple testing procedure with a 50% false discovery rate (FDR) identified associations least likely to be due to chance and those associations with more than two cases with the exposure and the anomaly were selected for further investigation. The methodology was evaluated by considering the detection of well-known teratogens.
RESULTS
The most common exposures were genitourinary system medications and sex hormones (35.2%), nervous system medications (28.0%) and anti-infectives for systemic use (25.7%). Fifty-two specific medication anomaly associations were identified. After discarding 10 overlapping and three protective associations, 39 associations were selected for further investigation. These associations included 16 which concerned well established teratogens, valproic acid (2) and maternal diabetes represented by use of insulin (14).
CONCLUSIONS
Medication exposure data in the EUROmediCAT central database can be analyzed systematically to determine a manageable set of associations for validation and then testing in independent datasets. Detection of teratogens depends on frequency of exposure, level of risk and teratogenic specificity.
Information about medication safety in pregnancy is inadequate. We aimed to develop a signal detection methodology to routinely identify unusual associations between medications and congenital anomalies using data collected by 15 European congenital anomaly registries.
METHODS
EUROmediCAT database data for 14 950 malformed foetuses/babies with first trimester medication exposures in 1995-2011 were analyzed. The odds of a specific medication exposure (coded according to chemical substance or subgroup) for a specific anomaly were compared with the odds of that exposure for all other anomalies for 40 385 medication anomaly combinations in the data. Simes multiple testing procedure with a 50% false discovery rate (FDR) identified associations least likely to be due to chance and those associations with more than two cases with the exposure and the anomaly were selected for further investigation. The methodology was evaluated by considering the detection of well-known teratogens.
RESULTS
The most common exposures were genitourinary system medications and sex hormones (35.2%), nervous system medications (28.0%) and anti-infectives for systemic use (25.7%). Fifty-two specific medication anomaly associations were identified. After discarding 10 overlapping and three protective associations, 39 associations were selected for further investigation. These associations included 16 which concerned well established teratogens, valproic acid (2) and maternal diabetes represented by use of insulin (14).
CONCLUSIONS
Medication exposure data in the EUROmediCAT central database can be analyzed systematically to determine a manageable set of associations for validation and then testing in independent datasets. Detection of teratogens depends on frequency of exposure, level of risk and teratogenic specificity.
- Language
-
- English
- Open access status
- bronze
- Identifiers
-
- DOI 10.1111/bcp.13056
- PMID 27353147
- Persistent URL
- https://sonar.ch/global/documents/79919
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