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Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials
BACKGROUND: COVID-19 is rapidly spreading causing extensive burdens across the world. Effective vaccines to prevent COVID-19 are urgently needed. METHODS AND FINDINGS: Our objective was to assess the effectiveness and safety of COVID-19 vaccines through analyses of all currently available randomized...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782520/ https://www.ncbi.nlm.nih.gov/pubmed/35061702 http://dx.doi.org/10.1371/journal.pone.0260733 |
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author | Korang, Steven Kwasi von Rohden, Elena Veroniki, Areti Angeliki Ong, Giok Ngalamika, Owen Siddiqui, Faiza Juul, Sophie Nielsen, Emil Eik Feinberg, Joshua Buron Petersen, Johanne Juul Legart, Christian Kokogho, Afoke Maagaard, Mathias Klingenberg, Sarah Thabane, Lehana Bardach, Ariel Ciapponi, Agustín Thomsen, Allan Randrup Jakobsen, Janus C. Gluud, Christian |
author_facet | Korang, Steven Kwasi von Rohden, Elena Veroniki, Areti Angeliki Ong, Giok Ngalamika, Owen Siddiqui, Faiza Juul, Sophie Nielsen, Emil Eik Feinberg, Joshua Buron Petersen, Johanne Juul Legart, Christian Kokogho, Afoke Maagaard, Mathias Klingenberg, Sarah Thabane, Lehana Bardach, Ariel Ciapponi, Agustín Thomsen, Allan Randrup Jakobsen, Janus C. Gluud, Christian |
author_sort | Korang, Steven Kwasi |
collection | PubMed |
description | BACKGROUND: COVID-19 is rapidly spreading causing extensive burdens across the world. Effective vaccines to prevent COVID-19 are urgently needed. METHODS AND FINDINGS: Our objective was to assess the effectiveness and safety of COVID-19 vaccines through analyses of all currently available randomized clinical trials. We searched the databases CENTRAL, MEDLINE, Embase, and other sources from inception to June 17, 2021 for randomized clinical trials assessing vaccines for COVID-19. At least two independent reviewers screened studies, extracted data, and assessed risks of bias. We conducted meta-analyses, network meta-analyses, and Trial Sequential Analyses (TSA). Our primary outcomes included all-cause mortality, vaccine efficacy, and serious adverse events. We assessed the certainty of evidence with GRADE. We identified 46 trials; 35 trials randomizing 219 864 participants could be included in our analyses. Our meta-analyses showed that mRNA vaccines (efficacy, 95% [95% confidence interval (CI), 92% to 97%]; 71 514 participants; 3 trials; moderate certainty); inactivated vaccines (efficacy, 61% [95% CI, 52% to 68%]; 48 029 participants; 3 trials; moderate certainty); protein subunit vaccines (efficacy, 77% [95% CI, −5% to 95%]; 17 737 participants; 2 trials; low certainty); and viral vector vaccines (efficacy 68% [95% CI, 61% to 74%]; 71 401 participants; 5 trials; low certainty) prevented COVID-19. Viral vector vaccines decreased mortality (risk ratio, 0.25 [95% CI 0.09 to 0.67]; 67 563 participants; 3 trials, low certainty), but comparable data on inactivated, mRNA, and protein subunit vaccines were imprecise. None of the vaccines showed evidence of a difference on serious adverse events, but observational evidence suggested rare serious adverse events. All the vaccines increased the risk of non-serious adverse events. CONCLUSIONS: The evidence suggests that all the included vaccines are effective in preventing COVID-19. The mRNA vaccines seem most effective in preventing COVID-19, but viral vector vaccines seem most effective in reducing mortality. Further trials and longer follow-up are necessary to provide better insight into the safety profile of these vaccines. |
format | Online Article Text |
id | pubmed-8782520 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-87825202022-01-22 Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials Korang, Steven Kwasi von Rohden, Elena Veroniki, Areti Angeliki Ong, Giok Ngalamika, Owen Siddiqui, Faiza Juul, Sophie Nielsen, Emil Eik Feinberg, Joshua Buron Petersen, Johanne Juul Legart, Christian Kokogho, Afoke Maagaard, Mathias Klingenberg, Sarah Thabane, Lehana Bardach, Ariel Ciapponi, Agustín Thomsen, Allan Randrup Jakobsen, Janus C. Gluud, Christian PLoS One Research Article BACKGROUND: COVID-19 is rapidly spreading causing extensive burdens across the world. Effective vaccines to prevent COVID-19 are urgently needed. METHODS AND FINDINGS: Our objective was to assess the effectiveness and safety of COVID-19 vaccines through analyses of all currently available randomized clinical trials. We searched the databases CENTRAL, MEDLINE, Embase, and other sources from inception to June 17, 2021 for randomized clinical trials assessing vaccines for COVID-19. At least two independent reviewers screened studies, extracted data, and assessed risks of bias. We conducted meta-analyses, network meta-analyses, and Trial Sequential Analyses (TSA). Our primary outcomes included all-cause mortality, vaccine efficacy, and serious adverse events. We assessed the certainty of evidence with GRADE. We identified 46 trials; 35 trials randomizing 219 864 participants could be included in our analyses. Our meta-analyses showed that mRNA vaccines (efficacy, 95% [95% confidence interval (CI), 92% to 97%]; 71 514 participants; 3 trials; moderate certainty); inactivated vaccines (efficacy, 61% [95% CI, 52% to 68%]; 48 029 participants; 3 trials; moderate certainty); protein subunit vaccines (efficacy, 77% [95% CI, −5% to 95%]; 17 737 participants; 2 trials; low certainty); and viral vector vaccines (efficacy 68% [95% CI, 61% to 74%]; 71 401 participants; 5 trials; low certainty) prevented COVID-19. Viral vector vaccines decreased mortality (risk ratio, 0.25 [95% CI 0.09 to 0.67]; 67 563 participants; 3 trials, low certainty), but comparable data on inactivated, mRNA, and protein subunit vaccines were imprecise. None of the vaccines showed evidence of a difference on serious adverse events, but observational evidence suggested rare serious adverse events. All the vaccines increased the risk of non-serious adverse events. CONCLUSIONS: The evidence suggests that all the included vaccines are effective in preventing COVID-19. The mRNA vaccines seem most effective in preventing COVID-19, but viral vector vaccines seem most effective in reducing mortality. Further trials and longer follow-up are necessary to provide better insight into the safety profile of these vaccines. Public Library of Science 2022-01-21 /pmc/articles/PMC8782520/ /pubmed/35061702 http://dx.doi.org/10.1371/journal.pone.0260733 Text en © 2022 Korang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Korang, Steven Kwasi von Rohden, Elena Veroniki, Areti Angeliki Ong, Giok Ngalamika, Owen Siddiqui, Faiza Juul, Sophie Nielsen, Emil Eik Feinberg, Joshua Buron Petersen, Johanne Juul Legart, Christian Kokogho, Afoke Maagaard, Mathias Klingenberg, Sarah Thabane, Lehana Bardach, Ariel Ciapponi, Agustín Thomsen, Allan Randrup Jakobsen, Janus C. Gluud, Christian Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials |
title | Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials |
title_full | Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials |
title_fullStr | Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials |
title_full_unstemmed | Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials |
title_short | Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials |
title_sort | vaccines to prevent covid-19: a living systematic review with trial sequential analysis and network meta-analysis of randomized clinical trials |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782520/ https://www.ncbi.nlm.nih.gov/pubmed/35061702 http://dx.doi.org/10.1371/journal.pone.0260733 |
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