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Abstract:
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In two harmonized AMP studies to prevent HIV infection through multiple infusions of a monoclonal antibody VRC01, a key objective is to evaluate whether drug concentration over time, is associated with the rate of HIV infection. Simulation studies are needed in the development of such survival models. We consider simulating event time data with a continuous time-varying covariate that varies with time not only through drug administration cycles, but also differently before and after a turning point within each cycle. We propose two simulation approaches: one based on simulating survival data under a single-dose regimen first before data are aggregated over multiple doses, and another based on simulating survival data directly under a multiple-dose regimen. We generate time-to-event data following a Cox proportional hazards (PH) model based on inverting the cumulative hazard function and a log link function for relating the hazard function to the covariates. The method validity is assessed in a set of simulation experiments, and results indicate that the proposed procedure performs well in producing data that conform to their cyclic nature and assumptions of the PH model.
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