Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
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
_version_ 1784638334637703168
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
work_keys_str_mv AT korangstevenkwasi vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT vonrohdenelena vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT veronikiaretiangeliki vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT onggiok vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT ngalamikaowen vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT siddiquifaiza vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT juulsophie vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT nielsenemileik vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT feinbergjoshuaburon vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT petersenjohannejuul vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT legartchristian vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT kokoghoafoke vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT maagaardmathias vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT klingenbergsarah vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT thabanelehana vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT bardachariel vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT ciapponiagustin vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT thomsenallanrandrup vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT jakobsenjanusc vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials
AT gluudchristian vaccinestopreventcovid19alivingsystematicreviewwithtrialsequentialanalysisandnetworkmetaanalysisofrandomizedclinicaltrials