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Drug Safety

, Volume 42, Issue 4, pp 499–513 | Cite as

Advances in Epidemiological Methods and Utilisation of Large Databases: A Methodological Review of Observational Studies on Central Nervous System Drug Use in Pregnancy and Central Nervous System Outcomes in Children

  • Zixuan Wang
  • Phoebe W. H. Ho
  • Michael T. H. Choy
  • Ian C. K. Wong
  • Ruth Brauer
  • Kenneth K. C. ManEmail author
Review Article
  • 155 Downloads

Abstract

Introduction

Studies have used various epidemiological approaches to study associations between central nervous system (CNS) drug use in pregnancy and CNS outcomes in children. Studies have generally focused on clinical adverse effects, whereas variations in methodologies have not received sufficient attention.

Objective

Our objective was to review the methodological characteristics of existing studies to identify any limitations and recommend further research.

Methods

A systematic literature search was conducted on observational studies listed in PubMed from 1 January 1946 to 21 September 2017. Following independent screening and data extraction, we conducted a review addressing the trends of relevant studies, differences between various data sources, and methods used to address bias and confounders; we also conducted statistical analyses.

Results

In total, 111 observational studies, 25 case–control studies, and 86 cohort studies were included in the review. Publications dating from 1978 to 2006 mainly focused on antiepileptic drugs, but research on antidepressants increased from 2007 onwards. Only one study focused on antipsychotic use during pregnancy. A total of 46 studies obtained data from an administrative database/registry, 20 from ad hoc disease registries, and 41 from ad hoc clinical samples. Most studies (58%) adjusted the confounding factors using general adjustment, whereas only a few studies used advanced methods such as sibling-matched models and propensity score methods; 42 articles used univariate analyses and 69 conducted multivariable regression analyses.

Conclusion

Multiple factors, including different study designs and data sources, have led to inconsistent findings in associations between CNS drug use in pregnancy and CNS outcomes in children. Researchers should allow for study designs with clearly defined exposure periods, at the very least in trimesters, and use advanced confounding adjustment methodology to increase the accuracy of the findings.

Notes

Acknowledgements

The authors thank Dr Elizabeth Jamieson, Dr Li Wei and Ms Lisa Wong for help with proofreading the manuscript.

Compliance with Ethical Standards

Funding

No sources of funding were used to conduct this study or prepare this manuscript.

Conflict of interest

Ian Wong has received grants from The Research Grants Council (Hong Kong), Innovative Medicines Initiative, Shire, Janssen-Cilag, Eli-Lily, Pfizer, and the European Union FP7 programme, outside the submitted work; was a member of the National Institute for Health and Care Excellence (NICE) ADHD Guideline Group and the British Association for Psychopharmacology ADHD guideline group and acted as an advisor to Shire. Kenneth Man and Ruth Brauer are recipients of the UCL CW Malpethorpe Fellowship. Kenneth Man has received personal fees from IQVIA Ltd, outside the submitted work. Zixuan Wang, Phoebe Ho, Michael Choy and Ruth Brauer have no other competing interests. No other relationships or activities could appear to have influenced the submitted work.

Supplementary material

40264_2018_755_MOESM1_ESM.pdf (723 kb)
Supplementary material 1 (PDF 723 kb)

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Zixuan Wang
    • 1
  • Phoebe W. H. Ho
    • 2
  • Michael T. H. Choy
    • 2
  • Ian C. K. Wong
    • 1
    • 2
  • Ruth Brauer
    • 1
  • Kenneth K. C. Man
    • 1
    • 2
    • 3
    Email author
  1. 1.Research Department of Practice and PolicyUCL School of PharmacyLondonUK
  2. 2.Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of MedicineThe University of Hong KongPok Fu LamHong Kong
  3. 3.Department of Medical InformaticsErasmus University Medical CenterRotterdamThe Netherlands

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