The analysis of survival data

In many cases, an endpoint measures time from the point of randomisation to some well-defined event, such as time to death in oncology or time to rash healing in herpes zoster. The data from such an endpoint invariably have a special feature known as censoring . Censoring in clinical trials usually occurs because the patient is still alive at the end of the period of follow-up. This chapter discusses Kaplan-Meier curves, which are used to display the data and to calculate summary statistics. It explains the logrank and Gehan-Wilcoxon tests, which are simple two-group comparisons for censored survival data, and extend these ideas to incorporate baseline covariates and factors. The chapter argues that calculating the mean is not possible in general because of censoring and that survival times/time to event values are not available for all subjects.