11/13/2015

Post date: Nov 16, 2015 3:07:03 PM

Title: Analysis of recurrent disease and overall survival in oncology studies

Speaker: Chiung-Yu Huang​, Division of Biostatistics and Bioinformatics, SKCCC, Johns Hopkins University

Abstract:

This talk considers nonparametric and semiparametric methods for studying recurrent disease and death with competing risks. I will first point out that comparisons based on the well-known cumulative incidence function can be confounded by different prevalence rates of the competing events, and that comparisons of the conditional distribution of the survival time given the failure event type are more relevant for investigating the prognosis of different patterns of recurrence disease. I then propose nonparametric estimators for the conditional cumulative incidence function as well as the conditional bivariate cumulative incidence function for the bivariate gap times, that is, the time to disease recurrence and the residual lifetime after recurrence. To quantify the association between the two gap times in the competing risks setting, a modified Kendall's tau statistic is proposed. The proposed estimators for the conditional bivariate cumulative incidence distribution and the association measure account for the induced dependent censoring for the second gap time. Hypothesis testing procedures for two-sample comparisons will be discussed. If time permits, I will also discuss regression analysis of the conditional cumulative incidence function using the semiparametric density ratio model.