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Stochastic interventional approach to assessing immune correlates of protection: Application to the COVE messenger RNA-1273 vaccine trial.
Hejazi, Nima S; Shen, Xiaoying; Carpp, Lindsay N; Benkeser, David; Follmann, Dean; Janes, Holly E; Baden, Lindsey R; El Sahly, Hana M; Deng, Weiping; Zhou, Honghong; Leav, Brett; Montefiori, David C; Gilbert, Peter B.
Afiliação
  • Hejazi NS; Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, USA.
  • Shen X; Department of Surgery and Duke Human Vaccine Institute, Duke University Medical Center, Durham, USA.
  • Carpp LN; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA.
  • Benkeser D; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, USA.
  • Follmann D; Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA.
  • 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.
  • Baden LR; Division of Infectious Diseases, Harvard Medical School, Brigham and Women's Hospital, Boston, USA.
  • El Sahly HM; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, USA.
  • Deng W; Infectious Disease Development, Moderna, Inc., Cambridge, USA.
  • Zhou H; Infectious Disease Development, Moderna, Inc., Cambridge, USA.
  • Leav B; Infectious Disease Development, Moderna, Inc., Cambridge, USA.
  • Montefiori DC; Department of Surgery and Duke Human Vaccine Institute, Duke University Medical Center, Durham, USA.
  • 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.
Int J Infect Dis ; 137: 28-39, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37820782
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.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 / 2_ODS3 / 4_TD Base de dados: MEDLINE Assunto principal: Vacinas / COVID-19 Tipo de estudo: Clinical_trials / Prognostic_studies Limite: Humans Idioma: En Revista: Int J Infect Dis Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 / 2_ODS3 / 4_TD Base de dados: MEDLINE Assunto principal: Vacinas / COVID-19 Tipo de estudo: Clinical_trials / Prognostic_studies Limite: Humans Idioma: En Revista: Int J Infect Dis Ano de publicação: 2023 Tipo de documento: Article