Stratified modestly-weighted log-rank tests in settings with an anticipated delayed separation of survival curves

TL;DR

This paper introduces stratified modestly-weighted log-rank tests tailored for survival analysis with delayed curve separation, enhancing efficiency by incorporating stratification in immuno-oncology studies.

Contribution

It combines weighted log-rank tests with stratification to improve detection of long-term survival benefits in delayed separation scenarios, addressing a gap in current methods.

Findings

Stratified weighted tests outperform unstratified ones in simulations.

Application to clinical trials demonstrates improved power.

Methods effectively handle delayed survival curve separation.

Abstract

Delayed separation of survival curves is a common occurrence in confirmatory studies in immuno-oncology. Many novel statistical methods that aim to efficiently capture potential long-term survival improvements have been proposed in recent years. However, the vast majority do not consider stratification, which is a major limitation considering that most (if not all) large confirmatory studies currently employ a stratified primary analysis. In this article, we combine recently proposed weighted log-rank tests that have been designed to work well under a delayed separation of survival curves, with stratification by a baseline variable. The aim is to increase the efficiency of the test when the stratifying variable is highly prognostic for survival. As there are many potential ways to combine the two techniques, we compare several possibilities in an extensive simulation study. We also apply the techniques retrospectively to two recent randomized clinical trials.