Detection and evaluation of signals associated with exposure to individual and combination of medications in pregnancy: A signal detection study protocol

Anuradhaa Subramanian, Siang Ing Lee, Sudasing Pathirannehelage Buddhika Hemali Sudasinghe, Steven Wambua, Katherine Phillips, Megha Singh, Amaya Azcoaga-Lorenzo, Neil Cockburn, Jingyan Wang, Adeniyi Francis Fagbamigbe, Muhammad Usman, Christine Damase-Michel, Christopher Yau, Lisa Kent, Colin McCowan, Dermot O’Reilly, Gillian SANTORELLI, Holly Hope, Jonathan I. Kennedy, Mohamed MhereegKathryn M Abel, Kelly-Ann Eastwood, Mairead Black, Maria Loane, Ngawai Moss, Sinead Brophy, Peter Brocklehurst, Helen Dolk, Catherine Nelson-Piercy , Krishnarajah Nirantharakumar

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Abstract

INTRODUCTION: Considering the high prevalence of polypharmacy in pregnant women and the knowledge gap in the risk-benefit safety profile of their often-complex treatment plan, more research is needed to optimise prescribing. In this study, we aim to detect adverse and protective effect signals of exposure to individual and pairwise combinations of medications during pregnancy. METHODS AND ANALYSIS: Using a range of real-world data sources from the UK, we aim to conduct a pharmacovigilance study to assess the safety of medications prescribed during the preconception period (3 months prior to conception) and first trimester of pregnancy. Women aged between 15 and 49 years with a record of pregnancy within the Clinical Practice Research Datalink (CPRD) Pregnancy Register, the Welsh Secure Anonymised Information Linkage (SAIL), the Scottish Morbidity Record (SMR) data sets and the Northern Ireland Maternity System (NIMATS) will be included. A series of case control studies will be conducted to estimate measures of disproportionality, detecting signals of association between a range of pregnancy outcomes and exposure to individual and combinations of medications. A multidisciplinary expert team will be invited to a signal detection workshop. By employing a structured framework, signals will be transparently assessed by each member of the team using a questionnaire appraising the signals on aspects of temporality, selection, time and measurement-related biases and confounding by underlying disease or comedications. Through group discussion, the expert team will reach consensus on each of the medication exposure-outcome signal, thereby excluding spurious signals, leaving signals suggestive of causal associations for further evaluation. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Independent Scientific Advisory Committee, SAIL Information Governance Review Panel, University of St. Andrews Teaching and Research Ethics Committee and Office for Research Ethics Committees Northern Ireland (ORECNI) for access and use of CPRD, SAIL, SMR and NIMATS data, respectively.

Original languageEnglish
Article numbere073162
Pages (from-to)1-11
Number of pages11
JournalBMJ Open
Volume13
Issue number10
Early online date9 Oct 2023
DOIs
Publication statusPublished online - 9 Oct 2023

Bibliographical note

Funding Information:
This work is independent research funded by the Strategic Priority Fund 'Tackling multimorbidity at scale' programme (grant number MR/W014432/1) delivered by the Medical Research Council and the National Institute for Health Research in partnership with the Economic and Social Research Council and in collaboration with the Engineering and Physical Sciences Research Council. The views expressed are those of the author and not necessarily those of the funders, the NIHR or the UK Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.This work was also supported by Health Data Research UK (HDRUK2023.0030), which is funded by UK Research and Innovation, the Medical Research Council, the British Heart Foundation, Cancer Research UK, the National Institute for Health and Care Research, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, Health and Care Research Wales, Health and Social Care Research and Development Division (Public Health Agency, Northern Ireland), Chief Scientist Office of the Scottish Government Health and Social Care Directorates

Publisher Copyright:
© 2023 BMJ Publishing Group. All rights reserved.

Keywords

  • epidemiology
  • maternal medicine
  • obstetrics

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