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

Nima S Hejazi; Xiaoying Shen; Lindsay N Carpp; David Benkeser; Dean Follmann; Holly E Janes; Lindsey R Baden; Hana M El Sahly; Weiping Deng; Honghong Zhou; Brett Leav; David C Montefiori; Peter B Gilbert

doi:10.1016/j.ijid.2023.09.012

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

Int J Infect Dis. 2023 Dec:137:28-39. doi: 10.1016/j.ijid.2023.09.012. Epub 2023 Oct 25.

Authors

Affiliations

¹ Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, USA.
² Department of Surgery and Duke Human Vaccine Institute, Duke University Medical Center, Durham, USA.
³ Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA.
⁴ Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, USA.
⁵ Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA.
⁶ 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.
⁷ Division of Infectious Diseases, Harvard Medical School, Brigham and Women's Hospital, Boston, USA.
⁸ Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, USA.
⁹ Infectious Disease Development, Moderna, Inc., Cambridge, USA.
¹⁰ 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: [email protected].

Abstract

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.

Keywords: Correlate of protection; Neutralizing antibody titer; Phase III trial; Stochastic interventional vaccine efficacy analysis.

Publication types

Clinical Trial, Phase III

MeSH terms

Antibodies, Neutralizing
Antibodies, Viral
COVID-19* / prevention & control
Humans
RNA, Messenger / genetics
Vaccines*

Substances

Antibodies, Neutralizing
Antibodies, Viral
RNA, Messenger
Vaccines

Abstract

Publication types

MeSH terms

Substances

Grants and funding