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Analyzing cellular immunogenicity in vaccine clinical trials: a new statistical method including non-specific responses for accurate estimation of vaccine effect

dc.rights.licenseopenen_US
hal.structure.identifierStatistics In System biology and Translational Medicine [SISTM]
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorLHOMME, Edouard
hal.structure.identifierStatistics In System biology and Translational Medicine [SISTM]
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorHEJBLUM, Boris
ORCID: 0000-0003-0646-452X
IDREF: 189970316
dc.contributor.authorLACABARATZ, C.
dc.contributor.authorWIEDEMANN, A.
dc.contributor.authorLELIEVRE, J. D.
dc.contributor.authorLEVY, Y.
hal.structure.identifierStatistics In System biology and Translational Medicine [SISTM]
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorTHIEBAUT, Rodolphe
hal.structure.identifierStatistics In System biology and Translational Medicine [SISTM]
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorRICHERT, Laura
dc.date.accessioned2021-02-03T14:27:32Z
dc.date.available2021-02-03T14:27:32Z
dc.date.issued2020
dc.identifier.issn1872-7905 (Electronic) 0022-1759 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/26124
dc.description.abstractEnEvaluation of immunogenicity is a key step in the clinical development of novel vaccines. T-cell responses to vaccine candidates are typically assessed by intracellular cytokine staining (ICS) using multiparametric flow cytometry. A conventional statistical approach to analyze ICS data is to compare, between vaccine regimens or between baseline and post-vaccination of the same regimen depending on the trial design, the percentages of cells producing a cytokine of interest after ex vivo stimulation of peripheral blood mononuclear cells (PBMC) with vaccine antigens, after subtracting the non-specific response (of unstimulated cells) of each sample. Subtraction of the non-specific response is aimed at capturing the specific response to the antigen, but raises methodological issues related to measurement error and statistical power. We describe here a new statistical approach to analyze ICS data from vaccine trials. We propose a bivariate linear regression model for estimating the non-specific and antigen-specific ICS responses. We benchmarked the performance of the model in terms of both bias and control of type-I and -II errors in comparison with conventional approaches, and applied it to simulated data as well as real pre- and post-vaccination data from two recent HIV vaccine trials (ANRS VRI01 in healthy volunteers and therapeutic VRI02 ANRS 149 LIGHT in HIV-infected participants). The model was as good as the conventional approaches (with or without subtraction of the non-specific response) in all simulation scenarios in terms of statistical performance, whereas the conventional approaches did not provide robust results across all scenarios. The proposed model estimated the T-cell responses to the antigens without any effect of the non-specific response on the specific response, irrespective of the correlation between the non-specific and specific responses. This novel method of analyzing T-cell immunogenicity data based on bivariate modeling is more flexible than conventional methods, and so yields more detailed results and enables accurate interpretation of vaccine-induced response.
dc.language.isoENen_US
dc.subjectSISTM
dc.title.enAnalyzing cellular immunogenicity in vaccine clinical trials: a new statistical method including non-specific responses for accurate estimation of vaccine effect
dc.title.alternativeJ Immunol Methodsen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.jim.2019.112711
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed31809708en_US
bordeaux.journalJournal of Immunological Methodsen_US
bordeaux.page112711en_US
bordeaux.volume477en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - U1219en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamSISTM_BPH
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03161945
hal.version1
hal.date.transferred2021-03-23T09:41:30Z
hal.exporttrue
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