The non-parametric interval estimation of the median survival time for the uncured population

Thomas M. Menino Convention & Exhibition Center 

In time-to-event data of recent cancer clinical trials, it is often the case that some patients never experience the event of interest even after a sufficiently long follow-up period. Patients who are not susceptible to the event of interest are considered cured, and the rest of the population uncured. Summarizing the data for the cured and uncured populations separately will help in understanding the data.
The median survival time is often used to summarize the survival time of the uncured population. In survival analysis with a cured population, parametric cure models are commonly used, and the median survival time for the uncured population is often estimated parametrically. A non-parametric estimate of the median survival time can be obtained without the risk of model misspecification. Maller and Zhou proposed a point estimate of a non-parametric survival function for the uncured population, but the interval estimation has not been detailed.
In this study, we approximated the standard error of the median survival time based on the Kaplan-Meier estimate using the delta method and constructed confidence intervals. We evaluated their performance via a Monte Carlo simulation.

Survival Analysis

Cure Model

Uncured Subpopulation

Median Survival Time

Non-Parametric Estimation 

Biometrics Section