Abstract
Vaccine clinical trials with active surveillance for infection often use the time to infection as the primary endpoint. A common method of analysis for such trials is to compare the times to infection between the vaccine and placebo groups using a Cox regression model. With new technology, we can sometimes additionally record the precise number of virions that cause infection rather than just the indicator that infection occurred. In this article, we develop a unified approach for vaccine trials that couples the time to infection with the number of infecting or founder viruses. We assume that the instantaneous risk of a potentially infectious exposure for individuals in the placebo and vaccine groups follows the same proportional intensity model. Following exposure, the number of founder viruses X* is assumed to be generated from some distribution on 0,1,…, which is allowed to be different for the two groups. Exposures that result in X*=0 are unobservable. We denote the placebo and vaccine means of X* by μ and μΔ so that 1-Δ measures the proportion reduction in the mean number of infecting virions due to vaccination per exposure. We develop different semi-parametric methods of estimating Δ. We allow the distribution of X* to be...Continue Reading
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Apr 14, 2016·Journal of Biomechanics·Brianne K ConnizzoLouis J Soslowsky
Jun 24, 2017·Biostatistics·Oliver Y ChénMartin A Lindquist
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