Bias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis

Using real-world data and past vaccination data, we conducted a large-scale experiment to quantify bias, precision and timeliness of different study designs to estimate historical background (expected) compared to post-vaccination (observed) rates of safety events for several vaccines. We used negat...

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Autores principales:	Xintong Li, Lana YH Lai, Anna Ostropolets, Faaizah Arshad, Eng Hooi Tan, Paula Casajust, Thamir M. Alshammari, Talita Duarte-Salles, Evan P. Minty, Carlos Areia, Nicole Pratt, Patrick B. Ryan, George Hripcsak, Marc A. Suchard, Martijn J. Schuemie, Daniel Prieto-Alhambra
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	incidence rate vaccine safety real world data empirical - comparison background rate Therapeutics. Pharmacology RM1-950
Acceso en línea:	https://doaj.org/article/7abbd4f540e14f1282e22242e106df3b
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spelling	oai:doaj.org-article:7abbd4f540e14f1282e22242e106df3b2021-11-30T19:18:55ZBias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis1663-981210.3389/fphar.2021.773875https://doaj.org/article/7abbd4f540e14f1282e22242e106df3b2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fphar.2021.773875/fullhttps://doaj.org/toc/1663-9812Using real-world data and past vaccination data, we conducted a large-scale experiment to quantify bias, precision and timeliness of different study designs to estimate historical background (expected) compared to post-vaccination (observed) rates of safety events for several vaccines. We used negative (not causally related) and positive control outcomes. The latter were synthetically generated true safety signals with incident rate ratios ranging from 1.5 to 4. Observed vs. expected analysis using within-database historical background rates is a sensitive but unspecific method for the identification of potential vaccine safety signals. Despite good discrimination, most analyses showed a tendency to overestimate risks, with 20%-100% type 1 error, but low (0% to 20%) type 2 error in the large databases included in our study. Efforts to improve the comparability of background and post-vaccine rates, including age-sex adjustment and anchoring background rates around a visit, reduced type 1 error and improved precision but residual systematic error persisted. Additionally, empirical calibration dramatically reduced type 1 to nominal but came at the cost of increasing type 2 error.Xintong LiLana YH LaiAnna OstropoletsFaaizah ArshadEng Hooi TanPaula CasajustThamir M. AlshammariTalita Duarte-SallesEvan P. MintyCarlos AreiaNicole PrattPatrick B. RyanPatrick B. RyanGeorge HripcsakGeorge HripcsakMarc A. SuchardMarc A. SuchardMartijn J. SchuemieMartijn J. SchuemieMartijn J. SchuemieDaniel Prieto-AlhambraDaniel Prieto-AlhambraFrontiers Media S.A.articleincidence ratevaccine safetyreal world dataempirical - comparisonbackground rateTherapeutics. PharmacologyRM1-950ENFrontiers in Pharmacology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	incidence rate vaccine safety real world data empirical - comparison background rate Therapeutics. Pharmacology RM1-950
spellingShingle	incidence rate vaccine safety real world data empirical - comparison background rate Therapeutics. Pharmacology RM1-950 Xintong Li Lana YH Lai Anna Ostropolets Faaizah Arshad Eng Hooi Tan Paula Casajust Thamir M. Alshammari Talita Duarte-Salles Evan P. Minty Carlos Areia Nicole Pratt Patrick B. Ryan Patrick B. Ryan George Hripcsak George Hripcsak Marc A. Suchard Marc A. Suchard Martijn J. Schuemie Martijn J. Schuemie Martijn J. Schuemie Daniel Prieto-Alhambra Daniel Prieto-Alhambra Bias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis
description	Using real-world data and past vaccination data, we conducted a large-scale experiment to quantify bias, precision and timeliness of different study designs to estimate historical background (expected) compared to post-vaccination (observed) rates of safety events for several vaccines. We used negative (not causally related) and positive control outcomes. The latter were synthetically generated true safety signals with incident rate ratios ranging from 1.5 to 4. Observed vs. expected analysis using within-database historical background rates is a sensitive but unspecific method for the identification of potential vaccine safety signals. Despite good discrimination, most analyses showed a tendency to overestimate risks, with 20%-100% type 1 error, but low (0% to 20%) type 2 error in the large databases included in our study. Efforts to improve the comparability of background and post-vaccine rates, including age-sex adjustment and anchoring background rates around a visit, reduced type 1 error and improved precision but residual systematic error persisted. Additionally, empirical calibration dramatically reduced type 1 to nominal but came at the cost of increasing type 2 error.
format	article
author	Xintong Li Lana YH Lai Anna Ostropolets Faaizah Arshad Eng Hooi Tan Paula Casajust Thamir M. Alshammari Talita Duarte-Salles Evan P. Minty Carlos Areia Nicole Pratt Patrick B. Ryan Patrick B. Ryan George Hripcsak George Hripcsak Marc A. Suchard Marc A. Suchard Martijn J. Schuemie Martijn J. Schuemie Martijn J. Schuemie Daniel Prieto-Alhambra Daniel Prieto-Alhambra
author_facet	Xintong Li Lana YH Lai Anna Ostropolets Faaizah Arshad Eng Hooi Tan Paula Casajust Thamir M. Alshammari Talita Duarte-Salles Evan P. Minty Carlos Areia Nicole Pratt Patrick B. Ryan Patrick B. Ryan George Hripcsak George Hripcsak Marc A. Suchard Marc A. Suchard Martijn J. Schuemie Martijn J. Schuemie Martijn J. Schuemie Daniel Prieto-Alhambra Daniel Prieto-Alhambra
author_sort	Xintong Li
title	Bias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis
title_short	Bias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis
title_full	Bias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis
title_fullStr	Bias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis
title_full_unstemmed	Bias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis
title_sort	bias, precision and timeliness of historical (background) rate comparison methods for vaccine safety monitoring: an empirical multi-database analysis
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/7abbd4f540e14f1282e22242e106df3b
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Bias, Precision and Timeliness of Historical (Background) Rate Comparison Methods for Vaccine Safety Monitoring: An Empirical Multi-Database Analysis

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