Stochastic interventional approach to assessing immune correlates of protection : Application to the COVE messenger RNA-1273 vaccine trial
Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved..
BACKGROUND: Stochastic interventional vaccine efficacy (SVE) analysis is a new approach to correlate of protection (CoP) analysis of a phase III trial that estimates how vaccine efficacy (VE) would change under hypothetical shifts of an immune marker.
METHODS: We applied nonparametric SVE methodology to the COVE trial of messenger RNA-1273 vs placebo to evaluate post-dose 2 pseudovirus neutralizing antibody (nAb) titer against the D614G strain as a CoP against COVID-19. Secondly, we evaluated the ability of these results to predict VE against variants based on shifts of geometric mean titers to variants vs D614G. Prediction accuracy was evaluated by 13 validation studies, including 12 test-negative designs.
RESULTS: SVE analysis of COVE supported post-dose 2 D614G titer as a CoP: estimated VE ranged from 66.9% (95% confidence interval: 36.2, 82.8%) to 99.3% (99.1, 99.4%) at 10-fold decreased or increased titer shifts, respectively. The SVE estimates only weakly predicted variant-specific VE estimates (concordance correlation coefficient 0.062 for post 2-dose VE).
CONCLUSION: SVE analysis of COVE supports nAb titer as a CoP for messenger RNA vaccines. Predicting variant-specific VE proved difficult due to many limitations. Greater anti-Omicron titers may be needed for high-level protection against Omicron vs anti-D614G titers needed for high-level protection against pre-Omicron COVID-19.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:137 |
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| Enthalten in: |
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases - 137(2023) vom: 06. Dez., Seite 28-39 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Hejazi, Nima S [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 15.12.2023 Date Revised 07.02.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.ijid.2023.09.012 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM363138323 |
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| 100 | 1 | |a Hejazi, Nima S |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Stochastic interventional approach to assessing immune correlates of protection |b Application to the COVE messenger RNA-1273 vaccine trial |
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| 500 | |a Date Revised 07.02.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved. | ||
| 520 | |a BACKGROUND: Stochastic interventional vaccine efficacy (SVE) analysis is a new approach to correlate of protection (CoP) analysis of a phase III trial that estimates how vaccine efficacy (VE) would change under hypothetical shifts of an immune marker | ||
| 520 | |a METHODS: We applied nonparametric SVE methodology to the COVE trial of messenger RNA-1273 vs placebo to evaluate post-dose 2 pseudovirus neutralizing antibody (nAb) titer against the D614G strain as a CoP against COVID-19. Secondly, we evaluated the ability of these results to predict VE against variants based on shifts of geometric mean titers to variants vs D614G. Prediction accuracy was evaluated by 13 validation studies, including 12 test-negative designs | ||
| 520 | |a RESULTS: SVE analysis of COVE supported post-dose 2 D614G titer as a CoP: estimated VE ranged from 66.9% (95% confidence interval: 36.2, 82.8%) to 99.3% (99.1, 99.4%) at 10-fold decreased or increased titer shifts, respectively. The SVE estimates only weakly predicted variant-specific VE estimates (concordance correlation coefficient 0.062 for post 2-dose VE) | ||
| 520 | |a CONCLUSION: SVE analysis of COVE supports nAb titer as a CoP for messenger RNA vaccines. Predicting variant-specific VE proved difficult due to many limitations. Greater anti-Omicron titers may be needed for high-level protection against Omicron vs anti-D614G titers needed for high-level protection against pre-Omicron COVID-19 | ||
| 650 | 4 | |a Clinical Trial, Phase III | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Correlate of protection | |
| 650 | 4 | |a Neutralizing antibody titer | |
| 650 | 4 | |a Phase III trial | |
| 650 | 4 | |a Stochastic interventional vaccine efficacy analysis | |
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| 650 | 7 | |a RNA, Messenger |2 NLM | |
| 650 | 7 | |a Vaccines |2 NLM | |
| 700 | 1 | |a Shen, Xiaoying |e verfasserin |4 aut | |
| 700 | 1 | |a Carpp, Lindsay N |e verfasserin |4 aut | |
| 700 | 1 | |a Benkeser, David |e verfasserin |4 aut | |
| 700 | 1 | |a Follmann, Dean |e verfasserin |4 aut | |
| 700 | 1 | |a Janes, Holly E |e verfasserin |4 aut | |
| 700 | 1 | |a Baden, Lindsey R |e verfasserin |4 aut | |
| 700 | 1 | |a El Sahly, Hana M |e verfasserin |4 aut | |
| 700 | 1 | |a Deng, Weiping |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Honghong |e verfasserin |4 aut | |
| 700 | 1 | |a Leav, Brett |e verfasserin |4 aut | |
| 700 | 1 | |a Montefiori, David C |e verfasserin |4 aut | |
| 700 | 1 | |a Gilbert, Peter B |e verfasserin |4 aut | |
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