Abstract summary 

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.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.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.

Authors & Co-authors:  Subramanian Anuradhaa A Lee Siang Ing SI Hemali Sudasinghe Sudasing Pathirannehelage Buddhika SPB Wambua Steven S Phillips Katherine K Singh Megha M Azcoaga-Lorenzo Amaya A Cockburn Neil N Wang Jingya J Fagbamigbe Adeniyi A Usman Muhammad M Damase-Michel Christine C Yau Christopher C Kent Lisa L McCowan Colin C OReilly Dermot D Santorelli Gillian G Hope Holly H Kennedy Jonathan J Mhereeg Mohamed M Abel Kathryn Mary KM Eastwood Kelly-Ann KA Black Mairead M Loane Maria M Moss Ngawai N Brophy Sinead S Brocklehurst Peter P Dolk Helen H Nelson-Piercy Catherine C Nirantharakumar Krishnarajah K

Study Outcome 

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