Abstract
Immunogenicity data from phase 1 vaccine studies can be difficult to interpret, especially in seropositive populations and when multiple assays are used. We developed 3 statistical methods (Youden index [YI] threshold, receiver-operating characteristic relative to baseline [ROC-B], and ROC of postdose levels [ROC-P]) to characterize complex immunogenicity data by assessing the proportion of a study population that achieved values above thresholds. The YI method calculates a single threshold per assay. Both ROC methods construct ROC curves for individual assays and surfaces for assay combinations to assess degree of separation of postdose values from a reference distribution; the ROC-B method uses overall predose values as the reference distribution and the ROC-P method uses pooled postdose values. All methods are applicable to a seropositive population with overlapping distributions of baseline and postdose measurements and can evaluate results of multiple assays jointly. The ROC-P method is also applicable when postdose levels are fully separated from baseline levels, as is common in a seronegative population. These methods were demonstrated using data from a phase 1a study of respiratory syncytial virus vaccines formulated with and without an adjuvant in a seropositive population of adults aged ≥60 years. All 3 methods provided a comprehensive assessment of vaccine immunogenicity effects with results presented in easily interpretable formats. In the example data, the methods demonstrated antigen dose response trend and contribution of adjuvant to response in multiple assays individually and jointly where optimal responses in assay combinations (humoral and cellular) are important.