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Abstract
CYD-TDV is the first licensed dengue vaccine for individuals 9–45 (or 60) years of age. Using 12% of the subjects enroled in phase-2b and phase-3 trials for which baseline serostatus was measured, the vaccine-induced protection against virologically confirmed dengue during active surveillance (0–25 months) was found to vary with prior exposure to dengue. Because age and dengue exposure are highly correlated in endemic settings, refined insight into how efficacy varies by serostatus and age is essential to understand the increased risk of hospitalisation observed among vaccinated individuals during the long-term follow-up and to develop safe and effective vaccination strategies. Here we apply machine learning to impute the baseline serostatus for subjects with post-dose 3 titres but missing baseline serostatus. We find evidence for age dependence in efficacy independent of serostatus and estimate that among 9–16 year olds, CYD-TDV is protective against serotypes 1, 3 and 4 regardless of baseline serostatus.
Highlights
The statistically significant differences in the proportions of cases and non-cases between subjects with known and unknown baseline serostatus in Honduras, the Philippines (p-value = 0.001, see Table 2) and in the Southeast Asian (CYD14) phase-3 trial (p-value = 0.019, see Table 2) are likely due to the lack of full randomisation in the assignment of a pre-defined number of subjects to the immunogenicity subsets in each site of the trials[15,16], which were instead established according to the time of subject enrolment in the trials, in a chronological fashion
The statistically significant difference observed in the proportions of cases with known or unknown baseline serostatus, among both subsets of subjects with known and unknown post-dose 3 (PD3) titres (p-values < 0.001, see Table 2), was due to the fact that the trial design specified that PD3 blood samples were retrospectively tested for dengue antibody levels for all dengue cases plus all participants in the immunological subsets of the trials
Our analysis shows that BRT, a machine learning algorithm, can impute the baseline serostatus of subjects with observed PD3 PRNT50 titres with high accuracy, using a dichotomous classification of the subjects into
Summary
Without stratifying by baseline serostatus and using either [2,3,4,5,6,7,8, 9,10,11, 12,13,14,15,16] or 2–8, 9–16 agegroups, we found a significant association (p-values < 0.0001, Fisher’s exact test), with more DENV2 and fewer DENV3 cases in the [2,3,4,5,6,7,8] age-group than expected and more DENV3 cases among [9,10,11] and 9–16-year olds than expected if age and serotype were independent (Supplementary Tables [3,4,5,6]).
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