Group sequential monitoring of years of life saved with paired censored survival data.

Abstract

This research develops non-parametric methodology for sequential monitoring of paired time-to-event data when comparing years of life saved, or years where any unpleasant outcome is delayed, is of interest. The recommended family of test statistics uses integrated differences in survival estimates that are available during the study period, where adjustments are made for dependence in the survival and censoring outcomes under comparison. In the context of paired censored survival data, the joint asymptotic closed form distribution of these sequentially monitored test statistics is developed and shown to have a dependent increments structure. Simulations verifying nice operating characteristics of the proposed monitoring methods also reveal consequences of ignoring an underlying paired data structure in terms of size and power properties. A motivating example is also presented via the Early Treatment Diabetic Retinopathy Study, which did not have methods available for sequentially monitoring paired censored survival data at the time.