title: A discrete-time survival model with random effects for designing and analyzing repeated low-dose challenge experiments.
abstract: Repeated low-dose (RLD) challenge designs are important in HIV vaccine research. Current methods for RLD designs rely heavily on an assumption of homogeneous risk of infection among animals, which, upon violation, can lead to invalid inferences and underpowered study designs. We propose to fit a discrete-time survival model with random effects that allows for heterogeneity in the risk of infection among animals and allows for predetermined challenge dose changes over time. Based on this model, we derive likelihood ratio tests and estimators for vaccine efficacy. A two-stage approach is proposed for optimizing the RLD design under cost constraints. Simulation studies demonstrate good finite sample properties of the proposed method and its superior performance compared to existing methods. We illustrate the application of the heterogeneous infection risk model on data from a real simian immunodeficiency virus vaccine study using Rhesus Macaques. The results of our study provide useful guidance for future RLD experimental design.
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
authors.forename: Chaeryon
authors.initials: C
authors.lastname: Kang
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA yhuang@fhcrc.org.
authors.forename: Ying
authors.initials: Y
authors.lastname: Huang
authors.affiliation: Center for Comparative Medicine and California National Primate Research Center, University of California, Davis, CA 95616, USA.
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Miller
mesh_terms: D000818:Animals; D015658:HIV Infections / Q000517:prevention & control*; D016013:Likelihood Functions; D008253:Macaca mulatta; D015233:Models, Statistical; D016019:Survival Analysis
keywords: Discrete-time survival model with random effects; HIV vaccine prevention research; Heterogeneous infection risk; Repeated low-dose challenge experiment; Sample size calculation