Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]

BACKGROUND: The COVID-19 vaccination program, which uses various types of vaccines, has been applied since the beginning of 2021. However, the efficacy in the context of seroconversion rate remains unclear. OBJECTIVE: To assess the seroconversion rates among different COVID-19 vaccines using a netwo...

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Main Authors: Gatot Soegiarto, -, Jonny Fajar, -, Laksmi Wulandari, -, Muhammad Anshory, -, Muhammad Ilmawan, -, Anisa Asmiragani, -, Himma Illiyana, -, Azaria Adam, -, Sutini Lamadi, -, Umi Sa'adah, -, Tubagus Yuantoko, -, Esi Nanda, -, Farida Rachmawati, -, Nabila Rahmadani, -, Randy Talilah, -, Madyline Katipana, -, Sharon Susanto, -, Maria Hindom, -, Ufi Anjasari, -, Nur Hidayah, -, Nanda Fadila, -, Vanela Lekatompessy, -, Uzi Phoenna, -, Fredo Tamara, -, Dessy Kartini, -, Aditya Mahendra, -, Andi Permana, -, Erwin Pasaribu, -, Kuldeep Dhama, -, Harapan, -
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Language:English
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Published: Taylor & Francis 2022
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Online Access:https://repository.unair.ac.id/119283/1/2.pdf
https://repository.unair.ac.id/119283/2/Artikel%201.pdf
https://repository.unair.ac.id/119283/3/Turnitin%20Artikel%201.pdf
https://repository.unair.ac.id/119283/
https://f1000research.com/articles/11-299/v1
https://doi.org/10.12688/f1000research.110281.1
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spelling id-langga.1192832022-12-24T11:53:12Z https://repository.unair.ac.id/119283/ Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations] Gatot Soegiarto, - Jonny Fajar, - Laksmi Wulandari, - Muhammad Anshory, - Muhammad Ilmawan, - Anisa Asmiragani, - Himma Illiyana, - Azaria Adam, - Sutini Lamadi, - Umi Sa'adah, - Tubagus Yuantoko, - Esi Nanda, - Farida Rachmawati, - Nabila Rahmadani, - Randy Talilah, - Madyline Katipana, - Sharon Susanto, - Maria Hindom, - Ufi Anjasari, - Nur Hidayah, - Nanda Fadila, - Vanela Lekatompessy, - Uzi Phoenna, - Fredo Tamara, - Dessy Kartini, - Aditya Mahendra, - Andi Permana, - Erwin Pasaribu, - Kuldeep Dhama, - Harapan, - R Medicine (General) RC Internal medicine BACKGROUND: The COVID-19 vaccination program, which uses various types of vaccines, has been applied since the beginning of 2021. However, the efficacy in the context of seroconversion rate remains unclear. OBJECTIVE: To assess the seroconversion rates among different COVID-19 vaccines using a network meta-analysis approach. METHODS: A network meta-analysis of randomized controlled trials (RCTs) was conducted during the study period. Data of interest, such as seroconversion rate and the type of COVID-19 vaccine, were extracted from each study. The analysis was performed using single-arm analysis by calculating the cumulative seroconversion rate. A network meta-analysis was conducted using the Bayesian method. RESULTS: A total of 31 RCTs were included in our analysis. Our pooled calculation revealed that the seroconversion rates of inactivated messenger ribonucleic acid (mRNA), protein subunit, and vector COVID-19 vaccines during the follow-up periods were 93.2%, 93.9%, 65.3%, and 54.7%, respectively, at ≤ 15 days; 96.0%, 94.8%, 91.2%, and 89.7%, respectively, between days 16–30; and 98.5%, 98.6%, 98.5%, and 96.2%, respectively, between days 31–60.The indirect comparison revealed that in the follow-up periods of ≤ 15 and 16–30 days, the inactivated and mRNA COVID-19 vaccines had superior seroconversion rates compared with those of the protein subunit and vector vaccines. In the follow-up period of 31–60 days, the highest seroconversion rates were found in the inactivated, mRNA, and protein subunit COVID-19 vaccines. CONCLUSION: This study provides valuable information regarding the comparison of seroconversion rates of COVID-19 vaccines. Taylor & Francis 2022 Article PeerReviewed text en https://repository.unair.ac.id/119283/1/2.pdf text en https://repository.unair.ac.id/119283/2/Artikel%201.pdf text en https://repository.unair.ac.id/119283/3/Turnitin%20Artikel%201.pdf Gatot Soegiarto, - and Jonny Fajar, - and Laksmi Wulandari, - and Muhammad Anshory, - and Muhammad Ilmawan, - and Anisa Asmiragani, - and Himma Illiyana, - and Azaria Adam, - and Sutini Lamadi, - and Umi Sa'adah, - and Tubagus Yuantoko, - and Esi Nanda, - and Farida Rachmawati, - and Nabila Rahmadani, - and Randy Talilah, - and Madyline Katipana, - and Sharon Susanto, - and Maria Hindom, - and Ufi Anjasari, - and Nur Hidayah, - and Nanda Fadila, - and Vanela Lekatompessy, - and Uzi Phoenna, - and Fredo Tamara, - and Dessy Kartini, - and Aditya Mahendra, - and Andi Permana, - and Erwin Pasaribu, - and Kuldeep Dhama, - and Harapan, - (2022) Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]. F1000Research, 11 (299). pp. 1-17. ISSN 2046-1402 https://f1000research.com/articles/11-299/v1 https://doi.org/10.12688/f1000research.110281.1
institution Universitas Airlangga
building Universitas Airlangga Library
continent Asia
country Indonesia
Indonesia
content_provider Universitas Airlangga Library
collection UNAIR Repository
language English
English
English
topic R Medicine (General)
RC Internal medicine
spellingShingle R Medicine (General)
RC Internal medicine
Gatot Soegiarto, -
Jonny Fajar, -
Laksmi Wulandari, -
Muhammad Anshory, -
Muhammad Ilmawan, -
Anisa Asmiragani, -
Himma Illiyana, -
Azaria Adam, -
Sutini Lamadi, -
Umi Sa'adah, -
Tubagus Yuantoko, -
Esi Nanda, -
Farida Rachmawati, -
Nabila Rahmadani, -
Randy Talilah, -
Madyline Katipana, -
Sharon Susanto, -
Maria Hindom, -
Ufi Anjasari, -
Nur Hidayah, -
Nanda Fadila, -
Vanela Lekatompessy, -
Uzi Phoenna, -
Fredo Tamara, -
Dessy Kartini, -
Aditya Mahendra, -
Andi Permana, -
Erwin Pasaribu, -
Kuldeep Dhama, -
Harapan, -
Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]
description BACKGROUND: The COVID-19 vaccination program, which uses various types of vaccines, has been applied since the beginning of 2021. However, the efficacy in the context of seroconversion rate remains unclear. OBJECTIVE: To assess the seroconversion rates among different COVID-19 vaccines using a network meta-analysis approach. METHODS: A network meta-analysis of randomized controlled trials (RCTs) was conducted during the study period. Data of interest, such as seroconversion rate and the type of COVID-19 vaccine, were extracted from each study. The analysis was performed using single-arm analysis by calculating the cumulative seroconversion rate. A network meta-analysis was conducted using the Bayesian method. RESULTS: A total of 31 RCTs were included in our analysis. Our pooled calculation revealed that the seroconversion rates of inactivated messenger ribonucleic acid (mRNA), protein subunit, and vector COVID-19 vaccines during the follow-up periods were 93.2%, 93.9%, 65.3%, and 54.7%, respectively, at ≤ 15 days; 96.0%, 94.8%, 91.2%, and 89.7%, respectively, between days 16–30; and 98.5%, 98.6%, 98.5%, and 96.2%, respectively, between days 31–60.The indirect comparison revealed that in the follow-up periods of ≤ 15 and 16–30 days, the inactivated and mRNA COVID-19 vaccines had superior seroconversion rates compared with those of the protein subunit and vector vaccines. In the follow-up period of 31–60 days, the highest seroconversion rates were found in the inactivated, mRNA, and protein subunit COVID-19 vaccines. CONCLUSION: This study provides valuable information regarding the comparison of seroconversion rates of COVID-19 vaccines.
format Article
PeerReviewed
author Gatot Soegiarto, -
Jonny Fajar, -
Laksmi Wulandari, -
Muhammad Anshory, -
Muhammad Ilmawan, -
Anisa Asmiragani, -
Himma Illiyana, -
Azaria Adam, -
Sutini Lamadi, -
Umi Sa'adah, -
Tubagus Yuantoko, -
Esi Nanda, -
Farida Rachmawati, -
Nabila Rahmadani, -
Randy Talilah, -
Madyline Katipana, -
Sharon Susanto, -
Maria Hindom, -
Ufi Anjasari, -
Nur Hidayah, -
Nanda Fadila, -
Vanela Lekatompessy, -
Uzi Phoenna, -
Fredo Tamara, -
Dessy Kartini, -
Aditya Mahendra, -
Andi Permana, -
Erwin Pasaribu, -
Kuldeep Dhama, -
Harapan, -
author_facet Gatot Soegiarto, -
Jonny Fajar, -
Laksmi Wulandari, -
Muhammad Anshory, -
Muhammad Ilmawan, -
Anisa Asmiragani, -
Himma Illiyana, -
Azaria Adam, -
Sutini Lamadi, -
Umi Sa'adah, -
Tubagus Yuantoko, -
Esi Nanda, -
Farida Rachmawati, -
Nabila Rahmadani, -
Randy Talilah, -
Madyline Katipana, -
Sharon Susanto, -
Maria Hindom, -
Ufi Anjasari, -
Nur Hidayah, -
Nanda Fadila, -
Vanela Lekatompessy, -
Uzi Phoenna, -
Fredo Tamara, -
Dessy Kartini, -
Aditya Mahendra, -
Andi Permana, -
Erwin Pasaribu, -
Kuldeep Dhama, -
Harapan, -
author_sort Gatot Soegiarto, -
title Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]
title_short Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]
title_full Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]
title_fullStr Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]
title_full_unstemmed Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]
title_sort seroconversion rates among different designs of covid-19 vaccines: a network meta-analysis of randomized controlled trials [version 1; peer review: 1 approved with reservations]
publisher Taylor & Francis
publishDate 2022
url https://repository.unair.ac.id/119283/1/2.pdf
https://repository.unair.ac.id/119283/2/Artikel%201.pdf
https://repository.unair.ac.id/119283/3/Turnitin%20Artikel%201.pdf
https://repository.unair.ac.id/119283/
https://f1000research.com/articles/11-299/v1
https://doi.org/10.12688/f1000research.110281.1
_version_ 1753808523049828352