Cargando…
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...
Autores principales: | , , , , , |
---|---|
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 |
_version_ | 1784858079806881792 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9785565 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT sonkyunghwa quantitativebenefitriskassessmentofcovid19vaccinesusingthemulticriteriadecisionanalysis AT kwonsunhong quantitativebenefitriskassessmentofcovid19vaccinesusingthemulticriteriadecisionanalysis AT nahyejung quantitativebenefitriskassessmentofcovid19vaccinesusingthemulticriteriadecisionanalysis AT baekyoungsuk quantitativebenefitriskassessmentofcovid19vaccinesusingthemulticriteriadecisionanalysis AT kiminok quantitativebenefitriskassessmentofcovid19vaccinesusingthemulticriteriadecisionanalysis AT leeeuikyung quantitativebenefitriskassessmentofcovid19vaccinesusingthemulticriteriadecisionanalysis |