Biased efficacy estimates in phase-III dengue vaccine trials due to heterogeneous exposure and differential detectability of primary infections across trial arms
Authored by Guido Espana, Cosmina Hogea, Adrienne Guignard, Bosch Quirine A ten, Amy C Morrison, David L Smith, Thomas W Scott, Alexander Schmidt, T Alex Perkins
Date Published: 2019
DOI: 10.1371/journal.pone.0210041
Sponsors:
United States National Institutes of Health (NIH)
Platforms:
C++
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
https://github.com/confunguido/dengueVaccineTrialHeterogeneities
Abstract
Vaccine efficacy (VE) estimates are crucial for assessing the
suitability of dengue vaccine candidates for public health
implementation, but efficacy trials are subject to a known bias to
estimate VE toward the null if heterogeneous exposure is not accounted
for in the analysis of trial data. In light of many well-characterized
sources of heterogeneity in dengue virus (DENV) transmission, our goal
was to estimate the potential magnitude of this bias in VE estimates for
a hypothetical dengue vaccine. To ensure that we realistically modeled
heterogeneous exposure, we simulated city-wide DENV transmission and
vaccine trial protocols using an agent-based model calibrated with
entomological and epidemiological data from long-term field studies in
Iquitos, Peru. By simulating a vaccine with a true VE of 0.8 in 1,000
replicate trials each designed to attain 90\% power, we found that
conventional methods underestimated VE by as much as 21\% due to
heterogeneous exposure. Accounting for the number of exposures in the
vaccine and placebo arms eliminated this bias completely, and the more
realistic option of including a frailty term to model exposure as a
random effect reduced this bias partially. We also discovered a distinct
bias in VE estimates away from the null due to lower detectability of
primary DENV infections among seronegative individuals in the vaccinated
group. This difference in detectability resulted from our assumption
that primary infections in vaccinees who are seronegative at baseline
resemble secondary infections, which experience a shorter window of
detectable viremia due to a quicker immune response. This resulted in an
artefactual finding that VE estimates for the seronegative group were
approximately 1\% greater than for the seropositive group. Simulation
models of vaccine trials that account for these factors can be used to
anticipate the extent of bias in field trials and to aid in their
interpretation.
Tags
Model
transmission
Population-dynamics
City
Iquitos
Vector
Puerto-rico
Aedes-aegypti diptera
Culicidae production