Confirmatory adaptive group sequential designs for single‐arm phase II studies with multiple time‐to‐event endpoints

Abstract

Existing methods concerning the assessment of long‐term survival outcomes in one‐armed trials are commonly restricted to one primary endpoint. Corresponding adaptive designs suffer from limitations regarding the use of information from other endpoints in interim design changes. Here we provide adaptive group sequential one‐sample tests for testing hypotheses on the multivariate survival distribution derived from multi‐state models, while making provision for data‐dependent design modifications based on all involved time‐to‐event endpoints. We explicitly elaborate application of the methodology to one‐sample tests for the joint distribution of (i) progression‐free survival (PFS) and overall survival (OS) in the context of an illness‐death model, and (ii) time to toxicity and time to progression while accounting for death as a competing event. Large sample distributions are derived using a counting process approach. Small sample properties are studied by simulation. An already established multi‐state model for non‐small cell lung cancer is used to illustrate the adaptive procedure.

Reference curve sampling variability in one–sample log–rank tests

“…Trial designs with interim analyses offering such kind of flexibility at full type I error rate control are commonly referred to as confirmatory adaptive designs [ 21 , 22 ]. Advanced one-sample methodology as in [ 23 ] might be transformed to be applicable in multi-arm settings in this way to address still existing problems when it comes to the use of additional information in interim analyses (see [ 24 ]).…”