Comparing and combining data from immune assays based on left-censored multivariate normal model assuming common assay differences across settings.

ABSTRACT: In vaccine research towards the prevention of infectious diseases, immune response biomarkers serve as an important tool for comparing and ranking vaccine candidates based on their immunogenicity and predicted protective effect. However, analyses of immune response outcomes can be complicated by differences across assays when immune response data are acquired from multiple groups/laboratories. Motivated by a real-world problem to accommodate the use of two different neutralization assays in COVID-19 vaccine trials, we propose methods based on left-censored multivariate normal model assuming common assay differences across settings, to adjust for differences between assays with respect to measurement error and the lower limit of detection. Our proposed methods integrate external paired-samp

SUBMITTER: Huang Y 

PROVIDER: S-EPMC9790822 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature