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Quantitative Benefit–Risk Assessment of COVID-19 Vaccines Using the Multi-Criteria Decision Analysis

In the early SARS-CoV-2 (COVID-19) pandemic, four major vaccines were approved despite limited efficacy and safety data through short regulatory review periods. Thus, it is necessary to assess the benefit-risk (BR) profiles of the COVID-19 vaccines. We conducted a quantitative BR assessment for four...

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Autores principales: Son, Kyung-Hwa, Kwon, Sun-Hong, Na, Hye-Jung, Baek, Youngsuk, Kim, Inok, Lee, Eui-Kyung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9785565/
https://www.ncbi.nlm.nih.gov/pubmed/36560439
http://dx.doi.org/10.3390/vaccines10122029
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author Son, Kyung-Hwa
Kwon, Sun-Hong
Na, Hye-Jung
Baek, Youngsuk
Kim, Inok
Lee, Eui-Kyung
author_facet Son, Kyung-Hwa
Kwon, Sun-Hong
Na, Hye-Jung
Baek, Youngsuk
Kim, Inok
Lee, Eui-Kyung
author_sort Son, Kyung-Hwa
collection PubMed
description In the early SARS-CoV-2 (COVID-19) pandemic, four major vaccines were approved despite limited efficacy and safety data through short regulatory review periods. Thus, it is necessary to assess the benefit-risk (BR) profiles of the COVID-19 vaccines. We conducted a quantitative BR assessment for four COVID-19 vaccines (mRNA-based: mRNA-1273 and BNT162b2; viral vector-based: Ad26.COV.2 and ChAdOx1-S) using multi-criteria decision analysis. Three benefit criteria and two risk criteria were considered: preventing COVID-19 infection for (1) adults aged ≥18 years; (2) seniors aged 60 years or older; and (3) severe COVID-19, adverse events (AEs), and serious AEs. Data were retrieved from clinical trials, observational studies, and county-specific AE monitoring reports. Based on the collected data, vaccines were scored for each criterion. 22 professionals weighted each criterion. The overall BR score was calculated using scores and weights. mRNA-1273 was the most preferred vaccine in pre-authorization and BNT162b2 in post-authorization. We found that the mRNA vaccine had a good balance between the benefits and risks. Using this BR assessment, the benefit-risk profile of COVID-19 vaccines can be updated with cumulated data. It will contribute to building evidence for decision making by policy makers and health professionals.
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spelling pubmed-97855652022-12-24 Quantitative Benefit–Risk Assessment of COVID-19 Vaccines Using the Multi-Criteria Decision Analysis Son, Kyung-Hwa Kwon, Sun-Hong Na, Hye-Jung Baek, Youngsuk Kim, Inok Lee, Eui-Kyung Vaccines (Basel) Article In the early SARS-CoV-2 (COVID-19) pandemic, four major vaccines were approved despite limited efficacy and safety data through short regulatory review periods. Thus, it is necessary to assess the benefit-risk (BR) profiles of the COVID-19 vaccines. We conducted a quantitative BR assessment for four COVID-19 vaccines (mRNA-based: mRNA-1273 and BNT162b2; viral vector-based: Ad26.COV.2 and ChAdOx1-S) using multi-criteria decision analysis. Three benefit criteria and two risk criteria were considered: preventing COVID-19 infection for (1) adults aged ≥18 years; (2) seniors aged 60 years or older; and (3) severe COVID-19, adverse events (AEs), and serious AEs. Data were retrieved from clinical trials, observational studies, and county-specific AE monitoring reports. Based on the collected data, vaccines were scored for each criterion. 22 professionals weighted each criterion. The overall BR score was calculated using scores and weights. mRNA-1273 was the most preferred vaccine in pre-authorization and BNT162b2 in post-authorization. We found that the mRNA vaccine had a good balance between the benefits and risks. Using this BR assessment, the benefit-risk profile of COVID-19 vaccines can be updated with cumulated data. It will contribute to building evidence for decision making by policy makers and health professionals. MDPI 2022-11-27 /pmc/articles/PMC9785565/ /pubmed/36560439 http://dx.doi.org/10.3390/vaccines10122029 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Son, Kyung-Hwa
Kwon, Sun-Hong
Na, Hye-Jung
Baek, Youngsuk
Kim, Inok
Lee, Eui-Kyung
Quantitative Benefit–Risk Assessment of COVID-19 Vaccines Using the Multi-Criteria Decision Analysis
title Quantitative Benefit–Risk Assessment of COVID-19 Vaccines Using the Multi-Criteria Decision Analysis
title_full Quantitative Benefit–Risk Assessment of COVID-19 Vaccines Using the Multi-Criteria Decision Analysis
title_fullStr Quantitative Benefit–Risk Assessment of COVID-19 Vaccines Using the Multi-Criteria Decision Analysis
title_full_unstemmed Quantitative Benefit–Risk Assessment of COVID-19 Vaccines Using the Multi-Criteria Decision Analysis
title_short Quantitative Benefit–Risk Assessment of COVID-19 Vaccines Using the Multi-Criteria Decision Analysis
title_sort quantitative benefit–risk assessment of covid-19 vaccines using the multi-criteria decision analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9785565/
https://www.ncbi.nlm.nih.gov/pubmed/36560439
http://dx.doi.org/10.3390/vaccines10122029
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