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A common feature of many recent trials evaluating the effects ofimmunotherapy on survival is that non-proportional hazards can be anticipatedat the design stage. This raises the possibility to use a statistical methodtailored towards testing the purported long-term benefit, rather than applyingthe more standard log-rank test and/or Cox model. Many such proposals have beenmade in recent years, but there remains a lack of practical guidance onimplementation, particularly in the context of group-sequential designs. Inthis article, we aim to fill this gap. We discuss how the POPLAR trial, whichcompared immunotherapy versus chemotherapy in non-small-cell lung cancer, mighthave been re-designed to be more robust to the presence of a delayed effect. Wethen provide step-by-step instructions on how to analyse a hypotheticalrealisation of the trial, based on this new design. Basic theory on weightedlog-rank tests and group-sequential methods is covered, and an accompanying Rpackage (including vignette) is provided.

Design and Analysis of group-sequential clinical trials based on a  modestly-weighted log-rank test in anticipation of a delayed separation of  survival curves: A practical guidance