4.8 Article

Refined efficacy estimates of the Sanofi Pasteur dengue vaccine CYD-TDV using machine learning

Journal

NATURE COMMUNICATIONS
Volume 9, Issue -, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41467-018-06006-6

Keywords

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Funding

  1. Imperial College Junior Research Fellowship scheme
  2. Bill and Melinda Gates Foundation
  3. National Institute of General Medical Sciences (NIGMS) 'Models of Infectious Disease Agent Study' (MIDAS) initiative
  4. UK Medical Research Council
  5. MRC [MR/R015600/1] Funding Source: UKRI

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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.

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