ADVANCE system testing: Estimating the incidence of adverse events following pertussis vaccination in healthcare databases with incomplete exposure data
Dodd, Caitlin; de Ridder, Maria; Weibel, Daniel; Mahaux, Olivia; Haguinet, Francois; de Smedt, Tom; de Lusignan, Simon; McGee, Chris; Duarte-Salles, Talita; Emborg, Hanne-Dorthe; Huerta-Alvarez, Consuelo; Martín-Merino, Elisa; Picelli, Gino; Berencsi, Klara; Danieli, Giorgia; Sturkenboom, Miriam
(2020) Vaccine, volume 38, pp. B47 - B55
(Article)
Abstract
The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private collaboration aiming to develop and test a system for rapid vaccine benefit-risk monitoring using existing European healthcare databases. Incidence rate (IR) estimates of vaccination-associated adverse events that are needed to model vaccination risks can be calculated from
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existing healthcare databases when vaccination (exposure) data are available. We assessed different methods to derive IRs in risk periods following vaccination when exposure data are missing in one database, using estimated IRs and IRRs from other databases for febrile seizures, fever and persistent crying. IRs were estimated for children aged 0-5 years in outcome-specific risk and non-risk periods following the first dose of acellular pertussis (aP) vaccination in four primary care databases and one hospital database. We compared derived and observed IRs in each database using three methods: 1) multiplication of non-risk period IR for database i by IR ratio (IRR) obtained from meta-analysis of IRRs estimated using the self-controlled case-series method, from databases other than i; 2) same method as 1, but multiplying with background IR; and 3) meta-analyses of observed IRs from databases other than i. IRs for febrile seizures were lower in primary care databases than the hospital database. The derived IR for febrile seizures using data from primary care databases was lower than that observed in the hospital database, and using data from the hospital database gave a higher derived IR than that observed in the primary care database. For fever and persistent crying the opposite was observed. We demonstrated that missing IRs for a post-vaccination period can be derived but that the type of database and the method of event data capture can have an impact on potential bias. We recommend IRs are derived using data from similar database types (hospital or primary care) with caution as even this can give heterogeneous results.
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Keywords: Child, Child, Preschool, Databases, Factual, Delivery of Health Care, Electronic Health Records, Europe, Humans, Incidence, Infant, Infant, Newborn, Vaccination/adverse effects, Whooping Cough/epidemiology, Adverse events following vaccination, Database heterogeneity, Missing exposure data, Incidence rate derivation, General Veterinary, Public Health, Environmental and Occupational Health, Infectious Diseases, Molecular Medicine, General Immunology and Microbiology, Research Support, Non-U.S. Gov't, Journal Article
ISSN: 0264-410X
Publisher: Elsevier
Note: Funding Information: The authors acknowledge input and guidance from Heather Whitaker (Open University, United Kingdom) and Paddy Farrington (Open University, United Kingdom). They acknowledge Bart Spiessens (Johnson & Johnson, Belgium) who authored the SAS code used to conduct the self-controlled case series. They also acknowledge medical writing and editorial assistance from Margaret Haugh (MediCom Consult, Villeurbanne, France). The results described in this publication are from the proof of concept studies conducted as part of the IMI ADVANCE project with the aim of testing the methodological aspects of the design, conduct and reporting of studies for vaccine benefit-risk monitoring activities. The results presented relate solely to the methodological testing and are not intended to inform regulatory or clinical decisions on the benefits and risks of the exposures under investigation. This warning should accompany any use of the results from these studies and they should be used accordingly. The views expressed in this article are the personal views of the authors and should not be understood or quoted as being made on behalf of or reflecting the position of the agencies or organisations with which the authors are affiliated. The Innovative Medicines Initiative Joint Undertaking funded this project under ADVANCE grant agreement n° 115557, resources of which were composed of a financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and in kind contributions from EFPIA member companies. Caitlin Dodd, Maria de Ridder, Tom de Smedt, Chris McGee, Talita Duarte-Salles, Hanne-Dorthe Emborg, Consuelo Huerta, Elisa Martín-Merino, Gino Picelli, Klara Berencsi, Giorgia Danieli declared that they have no potential conflicts of interest. Daniel Weibel declared that he has received personal fees from GSK for work unrelated to the submitted work. Olivia Mahaux and Francois Haguinet declared that they are employed by GSK and hold company shares. Simon de Lusignan declared that he has received grants from GSK, Takeda, and Seqirus / JSS, and also personal fees from Sequirus and Sanofi, for work unrelated to the submitted work. Miriam Sturkenboom declared that she has received grants from Novartis, CDC and Bill & Melinda Gates Foundation, for work unrelated to the submitted work. Publisher Copyright: © 2020 The Authors
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