A0259
Title: A R shiny tool TVCurve for visualizing survival analysis with time-varying covariate in oncology trials
Authors: Yimei Li - University of Pennsylvania (United States) [presenting]
Abstract: Survival analysis in clinical research often needs to evaluate the association between time-varying covariates (TVCs) and time-to-event endpoints. Existing methods to analyze TVCs included a naive approach (Kaplan-Meier [KM] method and Cox model), extended KM method, landmark analysis, and time-dependent (TD) Cox model. However, the pros and cons of various methods are underappreciated, and visualizing survival curves with TVCs is not always straightforward. An innovative R Shiny tool, TVCurve, is developed to provide a comprehensive suite for survival analysis with TVCs. The tool incorporates the methods noted above, and corresponding survival curves are generated. It also includes a parametric model with Weibull distributions. The tool builds in a simulation panel to allow a thorough evaluation of bias in the estimates under different methods. The use of the tool is demonstrated via applications to several clinical trials and conducted extensive simulations. A summary table of the observed patterns in simulation results is also provided as a quick reference for understanding the direction of bias and implication for study conclusions in clinical applications.
