Abstract

We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the parameters used and assess model performance. Our standard Poisson model, which includes a random per-person intercept to account for overdispersion, provided surprising findings: excess type I error (up to 28%) and poor coverage (~70%). A Poisson model with data-derived empirical variance structure, however, provided optimal power with type I error controlled at 5% and near 95% coverage. Explanations include that HSV detection frequency is doubly overdispersed: 1) person-level differences in shedding frequency must be accounted for by a random intercept and 2) the episodic nature of shedding induces additional extra-Poisson variance in person-level shedding frequency that must be accounted for using an empirical variance structure. These data support using the model with empirical variance structure for future crossover studies of HSV shedding.

Disciplines

Applied Statistics | Bioinformatics | Biometry | Biostatistics | Categorical Data Analysis | Clinical Epidemiology | Clinical Trials | Computational Biology | Design of Experiments and Sample Surveys | Disease Modeling | Epidemiology | Genetics | Genomics | Health Services Research | Institutional and Historical | Laboratory and Basic Science Research | Longitudinal Data Analysis and Time Series | Medical Specialties | Microarrays | Multivariate Analysis | Probability | Statistical Methodology | Statistical Models | Statistical Theory | Survival Analysis | Vital and Health Statistics

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