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Loss of power and clear description of treatment differences are key issuesin designing and analyzing a clinical trial where non-proportional hazard is apossibility. A log-rank test may be very inefficient and interpretation of thehazard ratio estimated using Cox regression is potentially problematic. In thiscase, the current ICH E9 (R1) addendum would suggest designing a trial with aclinically relevant estimand, e.g., expected life gain. This approach considersappropriate analysis methods for supporting the chosen estimand. However, suchan approach is case specific and may suffer lack of power for important choicesof the underlying alternate hypothesis distribution. On the other hand, theremay be a desire to have robust power under different deviations fromproportional hazards. Also, we would contend that no single number adequatelydescribes treatment effect under non-proportional hazards scenarios. Thecross-pharma working group has proposed a combination test to provide robustpower under a variety of alternative hypotheses. These can be specified forprimary analysis at the design stage and methods appropriately accounting forcombination test correlations are efficient for a variety of scenarios. We haveprovided design and analysis considerations based on a combination test underdifferent non-proportional hazard types and present a straw man proposal forpractitioners. The proposals are illustrated with real life example andsimulation.

Robust Design and Analysis of Clinical Trials With Non-proportional Hazards: A Straw Man Guidance from a Cross-pharma Working Group