Stochastic interventional approach to assessing immune correlates of protection: Application to the COVE messenger RNA-1273 vaccine trial.

Correlate of protection Neutralizing antibody titer Phase III trial Stochastic interventional vaccine efficacy analysis

Journal

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
ISSN: 1878-3511
Titre abrégé: Int J Infect Dis
Pays: Canada
ID NLM: 9610933

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 13 07 2023
revised: 30 08 2023
accepted: 17 09 2023
medline: 4 12 2023
pubmed: 12 10 2023
entrez: 11 10 2023
Statut: ppublish

Résumé

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. 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. 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). 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.

Sections du résumé

BACKGROUND 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 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 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 CONCLUSIONS
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.

Identifiants

pubmed: 37820782
pii: S1201-9712(23)00727-0
doi: 10.1016/j.ijid.2023.09.012
pii:
doi:

Substances chimiques

Antibodies, Neutralizing 0
RNA, Messenger 0
Vaccines 0
Antibodies, Viral 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

28-39

Subventions

Organisme : NIAID NIH HHS
ID : UM1 AI068635
Pays : United States

Informations de copyright

Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declarations of competing interest WD, HZ, and BL are employed by Moderna, Inc. and have stock and/or stock options in Moderna, Inc. DCM's laboratory receives funding from Moderna, Inc. to perform neutralizing antibody assays on serum samples from their clinical studies of COVID-19 vaccines.

Auteurs

Nima S Hejazi (NS)

Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, USA.

Xiaoying Shen (X)

Department of Surgery and Duke Human Vaccine Institute, Duke University Medical Center, Durham, USA.

Lindsay N Carpp (LN)

Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA.

David Benkeser (D)

Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, USA.

Dean Follmann (D)

Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA.

Holly E Janes (HE)

Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, USA; Department of Biostatistics, University of Washington, Seattle, USA.

Lindsey R Baden (LR)

Division of Infectious Diseases, Harvard Medical School, Brigham and Women's Hospital, Boston, USA.

Hana M El Sahly (HM)

Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, USA.

Weiping Deng (W)

Infectious Disease Development, Moderna, Inc., Cambridge, USA.

Honghong Zhou (H)

Infectious Disease Development, Moderna, Inc., Cambridge, USA.

Brett Leav (B)

Infectious Disease Development, Moderna, Inc., Cambridge, USA.

David C Montefiori (DC)

Department of Surgery and Duke Human Vaccine Institute, Duke University Medical Center, Durham, USA.

Peter B Gilbert (PB)

Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, USA; Department of Biostatistics, University of Washington, Seattle, USA. Electronic address: pgilbert@fredhutch.org.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH