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dc.contributor.authorLuteijn, JMen_US
dc.contributor.authorMorris, JKen_US
dc.contributor.authorGarne, Een_US
dc.contributor.authorGiven, Jen_US
dc.contributor.authorde Jong-van den Berg, Len_US
dc.contributor.authorAddor, M-Cen_US
dc.contributor.authorBakker, Men_US
dc.contributor.authorBarisic, Ien_US
dc.contributor.authorGatt, Men_US
dc.contributor.authorKlungsoyr, Ken_US
dc.contributor.authorLatos-Bielenska, Aen_US
dc.contributor.authorLelong, Nen_US
dc.contributor.authorNelen, Ven_US
dc.contributor.authorNeville, Aen_US
dc.contributor.authorO'Mahony, Men_US
dc.contributor.authorPierini, Aen_US
dc.contributor.authorTucker, Den_US
dc.contributor.authorde Walle, Hen_US
dc.contributor.authorWiesel, Aen_US
dc.contributor.authorLoane, Men_US
dc.contributor.authorDolk, Hen_US
dc.date.accessioned2018-06-26T09:59:04Z
dc.date.available2016-06-18en_US
dc.date.issued2016-10en_US
dc.date.submitted2018-06-05T16:10:47.389Z
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/40385
dc.description.abstractAIMS: 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.en_US
dc.description.sponsorshipEuropean Commission under the 7th Framework Program (grant agreement HEALTH-F5- 2011-260598).en_US
dc.format.extent1110 - 1122en_US
dc.languageengen_US
dc.language.isoenen_US
dc.relation.ispartofBr J Clin Pharmacolen_US
dc.subjectadverse drug reactionsen_US
dc.subjectcongenital anomaliesen_US
dc.subjectdrug safetyen_US
dc.subjectpharmacoepidemiologyen_US
dc.subjectpharmacovigilanceen_US
dc.subjectpregnancyen_US
dc.subjectAbnormalities, Drug-Induceden_US
dc.subjectAdulten_US
dc.subjectAdverse Drug Reaction Reporting Systemsen_US
dc.subjectCase-Control Studiesen_US
dc.subjectCongenital Abnormalitiesen_US
dc.subjectDatabases, Factualen_US
dc.subjectEuropeen_US
dc.subjectFemaleen_US
dc.subjectHumansen_US
dc.subjectPregnancyen_US
dc.subjectRegistriesen_US
dc.subjectTeratogensen_US
dc.subjectYoung Adulten_US
dc.titleEUROmediCAT signal detection: a systematic method for identifying potential teratogenic medication.en_US
dc.typeArticle
dc.identifier.doi10.1111/bcp.13056en_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/27353147en_US
pubs.issue4en_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.volume82en_US
dcterms.dateAccepted2016-06-18en_US


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