Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.

BACKGROUND: Establishing a large study network to conduct influenza vaccine effectiveness (IVE) studies while collecting appropriate variables to account for potential bias is important; the most relevant variables should be prioritized. We explored the impact of potential confounders on IVE in the...

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Autores: Stuurman AL, Levi M, Beutels P, Bricout H, Descamps A, Dos Santos G, McGovern I, Mira-Iglesias A, Nauta J, Torcel-Pagnon L, Biccler J
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Recursos:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
Repositorio:r-FISABIO. Repositorio Institucional de Producción Científica
OAI Identifier:oai:fisabio.fundanetsuite.com:p14347
Acesso em linha:https://fisabio.portalinvestigacion.com/publicaciones/14347
Access Level:acceso abierto
Palavra-chave:adjustment
confounders
covariate
influenza vaccine effectiveness
test-negative design
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spelling Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.Stuurman ALLevi MBeutels PBricout HDescamps ADos Santos GMcGovern IMira-Iglesias ANauta JTorcel-Pagnon LBiccler Jadjustmentconfounderscovariateinfluenza vaccine effectivenesstest-negative designBACKGROUND: Establishing a large study network to conduct influenza vaccine effectiveness (IVE) studies while collecting appropriate variables to account for potential bias is important; the most relevant variables should be prioritized. We explored the impact of potential confounders on IVE in the DRIVE multi-country network of sites conducting test-negative design (TND) studies. METHODS: We constructed a directed acyclic graph (DAG) to map the relationship between influenza vaccination, medically attended influenza infection, confounders, and other variables. Additionally, we used the Development of Robust and Innovative Vaccines Effectiveness (DRIVE) data from the 2018/2019 and 2019/2020 seasons to explore the effect of covariate adjustment on IVE estimates. The reference model was adjusted for age, sex, calendar time, and season. The covariates studied were presence of at least one, two, or three chronic diseases; presence of six specific chronic diseases; and prior healthcare use. Analyses were conducted by site and subsequently pooled. RESULTS: The following variables were included in the DAG: age, sex, time within influenza season and year, health status and comorbidities, study site, health-care-seeking behavior, contact patterns and social precautionary behavior, socioeconomic status, and pre-existing immunity. Across all age groups and settings, only adjustment for lung disease in older adults in the primary care setting resulted in a relative change of the IVE point estimate >10%. CONCLUSION: Our study supports a parsimonious approach to confounder adjustment in TND studies, limited to adjusting for age, sex, and calendar time. Practical implications are that necessitating fewer variables lowers the threshold for enrollment of sites in IVE studies and simplifies the pooling of data from different IVE studies or study networks.WILEY2023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://fisabio.portalinvestigacion.com/publicaciones/14347Influenza and Other Respiratory VirusesISSN: 17502640ISSNe: 17502659reponame:r-FISABIO. Repositorio Institucional de Producción Científicainstname:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)Inglésinfo:eu-repo/semantics/openAccessoai:fisabio.fundanetsuite.com:p143472026-06-11T12:45:17Z
dc.title.none.fl_str_mv Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.
title Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.
spellingShingle Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.
Stuurman AL
adjustment
confounders
covariate
influenza vaccine effectiveness
test-negative design
title_short Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.
title_full Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.
title_fullStr Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.
title_full_unstemmed Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.
title_sort Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.
dc.creator.none.fl_str_mv Stuurman AL
Levi M
Beutels P
Bricout H
Descamps A
Dos Santos G
McGovern I
Mira-Iglesias A
Nauta J
Torcel-Pagnon L
Biccler J
author Stuurman AL
author_facet Stuurman AL
Levi M
Beutels P
Bricout H
Descamps A
Dos Santos G
McGovern I
Mira-Iglesias A
Nauta J
Torcel-Pagnon L
Biccler J
author_role author
author2 Levi M
Beutels P
Bricout H
Descamps A
Dos Santos G
McGovern I
Mira-Iglesias A
Nauta J
Torcel-Pagnon L
Biccler J
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv adjustment
confounders
covariate
influenza vaccine effectiveness
test-negative design
topic adjustment
confounders
covariate
influenza vaccine effectiveness
test-negative design
description BACKGROUND: Establishing a large study network to conduct influenza vaccine effectiveness (IVE) studies while collecting appropriate variables to account for potential bias is important; the most relevant variables should be prioritized. We explored the impact of potential confounders on IVE in the DRIVE multi-country network of sites conducting test-negative design (TND) studies. METHODS: We constructed a directed acyclic graph (DAG) to map the relationship between influenza vaccination, medically attended influenza infection, confounders, and other variables. Additionally, we used the Development of Robust and Innovative Vaccines Effectiveness (DRIVE) data from the 2018/2019 and 2019/2020 seasons to explore the effect of covariate adjustment on IVE estimates. The reference model was adjusted for age, sex, calendar time, and season. The covariates studied were presence of at least one, two, or three chronic diseases; presence of six specific chronic diseases; and prior healthcare use. Analyses were conducted by site and subsequently pooled. RESULTS: The following variables were included in the DAG: age, sex, time within influenza season and year, health status and comorbidities, study site, health-care-seeking behavior, contact patterns and social precautionary behavior, socioeconomic status, and pre-existing immunity. Across all age groups and settings, only adjustment for lung disease in older adults in the primary care setting resulted in a relative change of the IVE point estimate >10%. CONCLUSION: Our study supports a parsimonious approach to confounder adjustment in TND studies, limited to adjusting for age, sex, and calendar time. Practical implications are that necessitating fewer variables lowers the threshold for enrollment of sites in IVE studies and simplifies the pooling of data from different IVE studies or study networks.
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://fisabio.portalinvestigacion.com/publicaciones/14347
url https://fisabio.portalinvestigacion.com/publicaciones/14347
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv WILEY
publisher.none.fl_str_mv WILEY
dc.source.none.fl_str_mv Influenza and Other Respiratory Viruses
ISSN: 17502640
ISSNe: 17502659
reponame:r-FISABIO. Repositorio Institucional de Producción Científica
instname:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
instname_str Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
reponame_str r-FISABIO. Repositorio Institucional de Producción Científica
collection r-FISABIO. Repositorio Institucional de Producción Científica
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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