Speaker
Description
The concept of interim analysis and adaption is more and more used in clinical trials. Furthermore, one often has several endpoints such as progression-free survival (PFS) and overall survival (OS) which is discussed in the current paper of Danzer et al. (2022). There, testing hypotheses with adaptive group sequential one-sample tests for the distribution of PFS and OS is developed. The authors assume entirely random censoring, but trials are often censored event-driven, both at the interim and at the final analysis. The aim of this work is to extend the current literature proposal for the PFS and OS model to such event-driven censoring in adaptive designs.
Using a purely counting-process oriented approach simplifies the notation and initially allows for general censoring mechanisms such as event-driven censoring.
In a simulation study, we compare our results using different approaches of event-driven censoring. By doing so, no negative effect can be detected.