EUROmediCAT signal detection: A systematic method for identifying potential teratogenic medication

Johannes M Luteijn, Joan Morris, Ester Garne, Joanne Given, Lolkje de Jong-van den Berg, Marie-Claude Addor, Marian Bakker, Ingeborg Barisic, Mariam Gatt, Kari Klungsoyr, Anna Latos-Bielenska, Nathalie Lelong, Vera Nelen, Amanda Neville, Mary O'Mahony, Anna Pierini, David Tucker, Hermien de Walle, Awi Wiesel, Maria Loane & 1 others Helen Dolk

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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 fetuses/babies with first trimester medication exposures in 1995-2011 were analysed. 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%). 52 specific medication-anomaly associations were identified. After discarding 10 overlapping and 3 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 analysed 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.
LanguageEnglish
Pages1110-1122
JournalBritish Journal of Clinical Pharmacology
Volume82
Issue number4
Early online date28 Jun 2016
DOIs
Publication statusE-pub ahead of print - 28 Jun 2016

Fingerprint

Teratogens
Databases
Urogenital System
Valproic Acid
Gonadal Steroid Hormones
First Pregnancy Trimester
Nervous System
Registries
Fetus
Mothers
Insulin
Safety
Pregnancy

Keywords

  • Pharmacovigilance
  • Congenital Anomalies
  • Adverse Drug Reactions
  • Pharmacoepidemiology
  • Pregnancy
  • Drug Safety

Cite this

Luteijn, Johannes M ; Morris, Joan ; Garne, Ester ; Given, Joanne ; de Jong-van den Berg, Lolkje ; Addor, Marie-Claude ; Bakker, Marian ; Barisic, Ingeborg ; Gatt, Mariam ; Klungsoyr, Kari ; Latos-Bielenska, Anna ; Lelong, Nathalie ; Nelen, Vera ; Neville, Amanda ; O'Mahony, Mary ; Pierini, Anna ; Tucker, David ; de Walle, Hermien ; Wiesel, Awi ; Loane, Maria ; Dolk, Helen. / EUROmediCAT signal detection: A systematic method for identifying potential teratogenic medication. In: British Journal of Clinical Pharmacology. 2016 ; Vol. 82, No. 4. pp. 1110-1122.
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title = "EUROmediCAT signal detection: A systematic method for identifying potential teratogenic medication",
abstract = "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 fetuses/babies with first trimester medication exposures in 1995-2011 were analysed. 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{\%}). 52 specific medication-anomaly associations were identified. After discarding 10 overlapping and 3 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 analysed 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.",
keywords = "Pharmacovigilance, Congenital Anomalies, Adverse Drug Reactions, Pharmacoepidemiology, Pregnancy, Drug Safety",
author = "Luteijn, {Johannes M} and Joan Morris and Ester Garne and Joanne Given and {de Jong-van den Berg}, Lolkje and Marie-Claude Addor and Marian Bakker and Ingeborg Barisic and Mariam Gatt and Kari Klungsoyr and Anna Latos-Bielenska and Nathalie Lelong and Vera Nelen and Amanda Neville and Mary O'Mahony and Anna Pierini and David Tucker and {de Walle}, Hermien and Awi Wiesel and Maria Loane and Helen Dolk",
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Luteijn, JM, Morris, J, Garne, E, Given, J, de Jong-van den Berg, L, Addor, M-C, Bakker, M, Barisic, I, Gatt, M, Klungsoyr, K, Latos-Bielenska, A, Lelong, N, Nelen, V, Neville, A, O'Mahony, M, Pierini, A, Tucker, D, de Walle, H, Wiesel, A, Loane, M & Dolk, H 2016, 'EUROmediCAT signal detection: A systematic method for identifying potential teratogenic medication', British Journal of Clinical Pharmacology, vol. 82, no. 4, pp. 1110-1122. https://doi.org/10.1111/bcp.13056

EUROmediCAT signal detection: A systematic method for identifying potential teratogenic medication. / Luteijn, Johannes M; Morris, Joan; Garne, Ester; Given, Joanne; de Jong-van den Berg, Lolkje; Addor, Marie-Claude; Bakker, Marian; Barisic, Ingeborg; Gatt, Mariam; Klungsoyr, Kari; Latos-Bielenska, Anna; Lelong, Nathalie; Nelen, Vera; Neville, Amanda; O'Mahony, Mary; Pierini, Anna; Tucker, David; de Walle, Hermien; Wiesel, Awi; Loane, Maria; Dolk, Helen.

In: British Journal of Clinical Pharmacology, Vol. 82, No. 4, 28.06.2016, p. 1110-1122.

Research output: Contribution to journalArticle

TY - JOUR

T1 - EUROmediCAT signal detection: A systematic method for identifying potential teratogenic medication

AU - Luteijn, Johannes M

AU - Morris, Joan

AU - Garne, Ester

AU - Given, Joanne

AU - de Jong-van den Berg, Lolkje

AU - Addor, Marie-Claude

AU - Bakker, Marian

AU - Barisic, Ingeborg

AU - Gatt, Mariam

AU - Klungsoyr, Kari

AU - Latos-Bielenska, Anna

AU - Lelong, Nathalie

AU - Nelen, Vera

AU - Neville, Amanda

AU - O'Mahony, Mary

AU - Pierini, Anna

AU - Tucker, David

AU - de Walle, Hermien

AU - Wiesel, Awi

AU - Loane, Maria

AU - Dolk, Helen

PY - 2016/6/28

Y1 - 2016/6/28

N2 - 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 fetuses/babies with first trimester medication exposures in 1995-2011 were analysed. 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%). 52 specific medication-anomaly associations were identified. After discarding 10 overlapping and 3 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 analysed 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.

AB - 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 fetuses/babies with first trimester medication exposures in 1995-2011 were analysed. 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%). 52 specific medication-anomaly associations were identified. After discarding 10 overlapping and 3 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 analysed 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.

KW - Pharmacovigilance

KW - Congenital Anomalies

KW - Adverse Drug Reactions

KW - Pharmacoepidemiology

KW - Pregnancy

KW - Drug Safety

U2 - 10.1111/bcp.13056

DO - 10.1111/bcp.13056

M3 - Article

VL - 82

SP - 1110

EP - 1122

JO - British Journal of Clinical Pharmacology

T2 - British Journal of Clinical Pharmacology

JF - British Journal of Clinical Pharmacology

SN - 0306-5251

IS - 4

ER -