The likelihood ratio function(LR)provides an easily interpretable measure for the value of risk prediction markers,and has been explored for both binary and continuous markers of a binary outcome(e.g.,diseased or not)(Gu and Pepe,2011).In this work,we extend the concept of LR to analyze survival outcomes that are subject to censoring.Estimation for the time-dependent LR(TD-LR)will be done using Kaplan-Meier estimation and a univariate Cox proportional hazards(PH)model to quantify the update of the risk prediction due to the knowledge of the marker value.