Graphical representation of survival curves in the presence of time-dependent categorical covariates with application to liver transplantation Abigail R. Smith Nathan P. Goodrich Charlotte A. Beil Qian Liu Robert M. Merion Brenda W. Gillespie Jarcy Zee 10.6084/m9.figshare.7491911.v1 https://tandf.figshare.com/articles/dataset/Graphical_representation_of_survival_curves_in_the_presence_of_time-dependent_categorical_covariates_with_application_to_liver_transplantation/7491911 <p>Graphical representation of survival curves is often used to illustrate associations between exposures and time-to-event outcomes. However, when exposures are time-dependent, calculation of survival probabilities is not straightforward. Our aim was to develop a method to estimate time-dependent survival probabilities and represent them graphically. Cox models with time-dependent indicators to represent state changes were fitted, and survival probabilities were plotted using pre-specified times of state changes. Time-varying hazard ratios for the state change were also explored. The method was applied to data from the Adult-to-Adult Living Donor Liver Transplantation Cohort Study (A2ALL). Survival curves showing a ‘split’ at a pre-specified time <i>t</i> allow for the qualitative comparison of survival probabilities between patients with similar baseline covariates who do and do not experience a state change at time <i>t</i>. Time since state change interactions can be visually represented to reflect changing hazard ratios over time. A2ALL study results showed differences in survival probabilities among those who did not receive a transplant, received a living donor transplant, and received a deceased donor transplant. These graphical representations of survival curves with time-dependent indicators improve upon previous methods and allow for clinically meaningful interpretation.</p> 2018-12-20 14:32:03 Cox regression graphing survival curves time-dependent covariate time-dependent interaction