Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials

Research output: Contribution to journalReviewResearchpeer-review

Standard

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.

In: PLoS ONE, Vol. 17, No. 1, e0260733, 2022.

Research output: Contribution to journalReviewResearchpeer-review

Harvard

Korang, SK, von Rohden, E, Veroniki, AA, Ong, G, Ngalamika, O, Siddiqui, F, Juul, S, Nielsen, EE, Feinberg, JB, Petersen, JJ, Legart, C, Kokogho, A, Maagaard, M, Klingenberg, S, Thabane, L, Bardach, A, Ciapponi, A, Thomsen, AR, Jakobsen, JC & Gluud, C 2022, 'Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials', PLoS ONE, vol. 17, no. 1, e0260733. https://doi.org/10.1371/journal.pone.0260733

APA

Korang, S. K., von Rohden, E., Veroniki, A. A., Ong, G., Ngalamika, O., Siddiqui, F., Juul, S., Nielsen, E. E., Feinberg, J. B., Petersen, J. J., Legart, C., Kokogho, A., Maagaard, M., Klingenberg, S., Thabane, L., Bardach, A., Ciapponi, A., Thomsen, A. R., Jakobsen, J. C., & Gluud, C. (2022). Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials. PLoS ONE, 17(1), [e0260733]. https://doi.org/10.1371/journal.pone.0260733

Vancouver

Korang SK, von Rohden E, Veroniki AA, Ong G, Ngalamika O, Siddiqui F et al. Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials. PLoS ONE. 2022;17(1). e0260733. https://doi.org/10.1371/journal.pone.0260733

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. / Vaccines to prevent COVID-19 : A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials. In: PLoS ONE. 2022 ; Vol. 17, No. 1.

Bibtex

@article{43f6241100494ce5a18b02d5f55ffb75,
title = "Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials",
abstract = "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. ",
author = "Korang, {Steven Kwasi} and {von Rohden}, Elena and Veroniki, {Areti Angeliki} and Giok Ong and Owen Ngalamika and Faiza Siddiqui and Sophie Juul and Nielsen, {Emil Eik} and Feinberg, {Joshua Buron} and Petersen, {Johanne Juul} and Christian Legart and Afoke Kokogho and Mathias Maagaard and Sarah Klingenberg and Lehana Thabane and Ariel Bardach and Agust{\'i}n Ciapponi and Thomsen, {Allan Randrup} and Jakobsen, {Janus C.} and Christian Gluud",
note = "Publisher Copyright: {\textcopyright} 2022 Korang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",
year = "2022",
doi = "10.1371/journal.pone.0260733",
language = "English",
volume = "17",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "1",

}

RIS

TY - JOUR

T1 - Vaccines to prevent COVID-19

T2 - A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials

AU - Korang, Steven Kwasi

AU - von Rohden, Elena

AU - Veroniki, Areti Angeliki

AU - Ong, Giok

AU - Ngalamika, Owen

AU - Siddiqui, Faiza

AU - Juul, Sophie

AU - Nielsen, Emil Eik

AU - Feinberg, Joshua Buron

AU - Petersen, Johanne Juul

AU - Legart, Christian

AU - Kokogho, Afoke

AU - Maagaard, Mathias

AU - Klingenberg, Sarah

AU - Thabane, Lehana

AU - Bardach, Ariel

AU - Ciapponi, Agustín

AU - Thomsen, Allan Randrup

AU - Jakobsen, Janus C.

AU - Gluud, Christian

N1 - Publisher Copyright: © 2022 Korang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

U2 - 10.1371/journal.pone.0260733

DO - 10.1371/journal.pone.0260733

M3 - Review

C2 - 35061702

AN - SCOPUS:85123307523

VL - 17

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 1

M1 - e0260733

ER -

ID: 291221905