Academic Journal
Analyzing cellular immunogenicity in vaccine clinical trials: a new statistical method including non-specific responses for accurate estimation of vaccine effect ; J Immunol Methods
| العنوان: | Analyzing cellular immunogenicity in vaccine clinical trials: a new statistical method including non-specific responses for accurate estimation of vaccine effect ; J Immunol Methods |
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| المؤلفون: | LHOMME, Edouard, HEJBLUM, Boris, LACABARATZ, C., WIEDEMANN, A., LELIEVRE, J. D., LEVY, Y., THIEBAUT, Rodolphe, RICHERT, Laura |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | SISTM, Sciences du Vivant [q-bio]/Santé publique et épidémiologie |
| الوصف: | Evaluation 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 ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | 1872-7905 (Electronic) 0022-1759 (Linking); https://oskar-bordeaux.fr/handle/20.500.12278/26124 |
| DOI: | 10.1016/j.jim.2019.112711 |
| الاتاحة: | https://oskar-bordeaux.fr/handle/20.500.12278/26124 https://hdl.handle.net/20.500.12278/26124 https://doi.org/10.1016/j.jim.2019.112711 |
| Rights: | open |
| رقم الانضمام: | edsbas.FEAA3E75 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.jim.2019.112711 |
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