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Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials
Several vaccines have been approved for the prevention of COVID-19. However, no head-to-head trials comparing their clinical efficacy have been performed. This network meta-analysis aims to identify those, among the competing existing vaccines, conferring the maximum protection against COVID-19. A l...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640819/ https://www.ncbi.nlm.nih.gov/pubmed/36342658 http://dx.doi.org/10.1007/s43440-022-00429-1 |
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author | Kumar, Subodh Saikia, Dibyajyoti Bankar, Mangesh Saurabh, Manoj Kumar Singh, Harminder Varikasuvu, Sheshadri Reddy Maharshi, Vikas |
author_facet | Kumar, Subodh Saikia, Dibyajyoti Bankar, Mangesh Saurabh, Manoj Kumar Singh, Harminder Varikasuvu, Sheshadri Reddy Maharshi, Vikas |
author_sort | Kumar, Subodh |
collection | PubMed |
description | Several vaccines have been approved for the prevention of COVID-19. However, no head-to-head trials comparing their clinical efficacy have been performed. This network meta-analysis aims to identify those, among the competing existing vaccines, conferring the maximum protection against COVID-19. A literature search was done in Medline (via PubMed), Embase and Cochrane Library databases for phase 3 randomized controlled trials evaluating the efficacy of different COVID-19 vaccines. Search results were screened and eligible studies were included to perform a network meta-analysis in software ‘R’ version 4.1.2 using a random effect model. Cochrane’s ‘Risk of Bias tool (RoB2)’ was used for quality assessment. Raw data from the included studies was used for network meta-analysis. Assessment of inconsistency was not possible as no study compared two or more vaccines directly. A forest plot for indirect comparison of various COVID-19 vaccines was obtained. Rankogram and ‘P’ scores were obtained to rank the vaccines based on the indirect evidence of their comparative efficacy. A total of 17 randomized controlled trials evaluating the efficacy of 16 COVID-19 vaccines, were included in the network meta-analysis. A total of 361,386 participants was included in this network meta-analysis. Overall risk of bias among included studies was of ‘some concern’. All the COVID-19 vaccines had a statistically significant reduction of risk for contracting symptomatic SARS-CoV-2 in comparison to the placebo, however, the maximum protection (RR 0.05) was with BNT126b2. The indirect comparison also revealed BNT126b2 vaccine confers the highest protection against symptomatic SARS-CoV-2 infection in comparison to all others included, with a ‘P’ score of 0.9771 followed by mRNA-1273, rAD26 & rAD5 and NVX-CoV2373. The evidence generated from this network meta-analysis indicates the good efficacy of all the included vaccines in preventing symptomatic COVID-19 as compared to placebo. The BNT126b2 vaccine was found to provide the highest protection against symptomatic SARS-CoV-2 among all included followed by mRNA-1273, rAD26 & rAD5, NVX-CoV2373 and others. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43440-022-00429-1. |
format | Online Article Text |
id | pubmed-9640819 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-96408192022-11-14 Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials Kumar, Subodh Saikia, Dibyajyoti Bankar, Mangesh Saurabh, Manoj Kumar Singh, Harminder Varikasuvu, Sheshadri Reddy Maharshi, Vikas Pharmacol Rep Special Issue: Review Several vaccines have been approved for the prevention of COVID-19. However, no head-to-head trials comparing their clinical efficacy have been performed. This network meta-analysis aims to identify those, among the competing existing vaccines, conferring the maximum protection against COVID-19. A literature search was done in Medline (via PubMed), Embase and Cochrane Library databases for phase 3 randomized controlled trials evaluating the efficacy of different COVID-19 vaccines. Search results were screened and eligible studies were included to perform a network meta-analysis in software ‘R’ version 4.1.2 using a random effect model. Cochrane’s ‘Risk of Bias tool (RoB2)’ was used for quality assessment. Raw data from the included studies was used for network meta-analysis. Assessment of inconsistency was not possible as no study compared two or more vaccines directly. A forest plot for indirect comparison of various COVID-19 vaccines was obtained. Rankogram and ‘P’ scores were obtained to rank the vaccines based on the indirect evidence of their comparative efficacy. A total of 17 randomized controlled trials evaluating the efficacy of 16 COVID-19 vaccines, were included in the network meta-analysis. A total of 361,386 participants was included in this network meta-analysis. Overall risk of bias among included studies was of ‘some concern’. All the COVID-19 vaccines had a statistically significant reduction of risk for contracting symptomatic SARS-CoV-2 in comparison to the placebo, however, the maximum protection (RR 0.05) was with BNT126b2. The indirect comparison also revealed BNT126b2 vaccine confers the highest protection against symptomatic SARS-CoV-2 infection in comparison to all others included, with a ‘P’ score of 0.9771 followed by mRNA-1273, rAD26 & rAD5 and NVX-CoV2373. The evidence generated from this network meta-analysis indicates the good efficacy of all the included vaccines in preventing symptomatic COVID-19 as compared to placebo. The BNT126b2 vaccine was found to provide the highest protection against symptomatic SARS-CoV-2 among all included followed by mRNA-1273, rAD26 & rAD5, NVX-CoV2373 and others. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43440-022-00429-1. Springer International Publishing 2022-11-07 2022 /pmc/articles/PMC9640819/ /pubmed/36342658 http://dx.doi.org/10.1007/s43440-022-00429-1 Text en © The Author(s) under exclusive licence to Maj Institute of Pharmacology Polish Academy of Sciences 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Special Issue: Review Kumar, Subodh Saikia, Dibyajyoti Bankar, Mangesh Saurabh, Manoj Kumar Singh, Harminder Varikasuvu, Sheshadri Reddy Maharshi, Vikas Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials |
title | Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials |
title_full | Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials |
title_fullStr | Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials |
title_full_unstemmed | Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials |
title_short | Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials |
title_sort | efficacy of covid-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials |
topic | Special Issue: Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640819/ https://www.ncbi.nlm.nih.gov/pubmed/36342658 http://dx.doi.org/10.1007/s43440-022-00429-1 |
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