Evidence map›Paper›PMID 27353147›Full record

ArticleBritish journal of clinical pharmacology2016

EUROmediCAT signal detection: a systematic method for identifying potential teratogenic medication.

Johannes M Luteijn, Joan K Morris, Ester Garne, Joanne Given, Lolkje de Jong-van den Berg, Marie-Claude Addor, Marian Bakker, Ingeborg Barisic, Miriam Gatt, Kari Klungsoyr and 11 more

Abstract read
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Article in British journal of clinical pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Johannes M LuteijnWolfson Institute of Preventive Medicine, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Joan K MorrisWolfson 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.
Ester GarnePaediatric Department, Hospital Lillebaelt, Kolding, Denmark.
Joanne GivenCentre for Maternal, Fetal and Infant Research, Institute of Nursing and Health Research, Ulster University, Newtownabbey, UK.
Lolkje de Jong-van den BergDepartment of Pharmacy, Unit of PharmacoEpidemiology and PharmacoEconomics, Groningen, The Netherlands.
Marie-Claude AddorDivision of Medical Genetics, CHUV, Lausanne, Switzerland.
Marian BakkerUniversity Medical Centre of Groningen, Groningen, The Netherlands.
Ingeborg BarisicDepartment of Medical Genetics and Reproductive Health, Children's Hospital Zagreb, Medical School University of Zagreb, Zagreb, Croatia.
Miriam GattDepartment of Health Information and Research, Guardamangia, Malta.
Kari KlungsoyrMedical Birth Registry of Norway, The Norwegian Institute of Public Health and Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
Anna Latos-BielenskaDepartment of Medical Genetics, Poznan University of Medical Sciences, Poznan, Poland.
Nathalie LelongCenter for biostatistics and epidemiology, INSERM U1153, Paris, France.
Vera NelenProvinciaal Instituut voor Hygiene (PIH), Antwerp, Belgium.
Amanda NevilleIMER Registry (Emila Romagna Registry of Birth Defects), Center for Clinical and Epidemiological Research University of Ferrara and Azienda Ospedaliero- Universitaria di Ferrara, Ferrara, Italy.
Mary O'MahonyPublic Health Medicine, Health Service Executive, Cork, Ireland.
Anna PieriniNational Research Council (IFC-CNR), Institute of Clinical Pharmacology, Pisa, Italy.
David TuckerCongenital Anomaly Register and Information Service for Wales, Public Health Wales, Swansea, UK.
Hermien de WalleDepartment of Genetics, EUROCAT Northern Netherlands, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Awi WieselMainz Model Birth Registry, University Children's Hospital Mainz, Germany.
Maria LoaneCentre for Maternal, Fetal and Infant Research, Institute of Nursing and Health Research, Ulster University, Newtownabbey.
Helen DolkCentre for Maternal, Fetal and Infant Research, Institute of Nursing and Health Research, Ulster University, Newtownabbey, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsInformation 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.

methodsEUROmediCAT 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.

resultsThe 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).

conclusionsMedication 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.

Indexed as

TeratogensAbnormalities, Drug-InducedAdultAdverse Drug Reaction Reporting SystemsCase-Control StudiesCongenital AbnormalitiesDatabases, FactualEuropeFemaleHumansPregnancyRegistriesYoung AdultTeratogensadverse drug reactionscongenital anomaliesdrug safetypharmacoepidemiologypharmacovigilancepregnancy

Identifiers

PMID27353147
PMCPMC5137836

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.