Implementing near real-time vaccine safety surveillance using the Clinical Practice Research Datalink (CPRD)

Andreia Leite*, Sara L. Thomas, Nick J. Andrews

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Introduction Near real-time vaccine safety surveillance (NRTVSS) using electronic health records is increasingly used to rapidly detect vaccine safety signals. NRTVSS has not been fully implemented in the UK. We assessed the feasibility of implementing this surveillance using the UK Clinical Practice Research Datalink (CPRD). Methods We selected seasonal influenza vaccine/Guillain-Barré Syndrome (GBS) as an example of a rare outcome and measles-mumps-rubella (MMR) vaccine/febrile seizures as a positive control. For influenza/GBS we implemented a system for the 2013/2014 and 2014/2015 influenza seasons; for MMR/seizures the surveillance period was July 2014–June 2015. We used the continuous Poisson-based maximized sequential probability ratio test (PMaxSPRT), comparing observed-to-expected events, for both pairs. We calculated an age-sex-adjusted rate using 5 years of historic data and used this rate to calculate the expected number of events in pre-specified post-vaccination risk-window (GBS: 0–42 days, seizures: 6–21 days). For MMR/seizures we also implemented the system using the Binominal-based maximized sequential probability ratio test (BMaxSPRT). For this, we compared seizures in the risk-window (6–21 days) to a control window (0–5 and 22–32 days). Delays in recording outcomes influence the data available, so we adjusted the expected number of events using a historical distribution of delays in recording GBS/febrile seizures. Analyses were run using data up to each CPRD monthly release. We also performed power calculations for detecting increases in relative risk (RR) from 1.5 to 10. Results For influenza/GBS we implemented a system in both seasons with no signal. Power to detect a signal was >80% for RR ≥ 4. For MMR/seizures we were able to identify a signal with PMaxSPRT but not with BMaxSPRT. Power ≥ 80% for RR ≥ 2.5 for both tests. Conclusion CPRD is a potential data source to implement NRTVSS to exclude large increases in the risk of rare outcomes after seasonal influenza and lower increases in risk for more frequent outcomes.

Original languageEnglish
Pages (from-to)6885-6892
Number of pages8
JournalVaccine
Volume35
Issue number49
DOIs
Publication statusPublished - 14 Dec 2017

Bibliographical note

Funding Information:
The authors would like to thank Dr. Ivair Silva, for promptly replying to queries related with the use of the R package Sequential, and to Dr. Jemma Walker, for sharing an algorithm to identify individuals vaccinated with MMR. The research was funded by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Immunisation at the London School of Hygiene and Tropical Medicine in partnership with Public Health England. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or Public Health England. The funders had no role in the study design, data collection, analysis, or interpretation.

Publisher Copyright:
© 2017 The Authors

Keywords

  • Electronic health records
  • Safety
  • Surveillance
  • Timeliness
  • Vaccines

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