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Testing Treatment Effect in Randomized Clinical Trials With Possible Nonproportional Hazards

ABSTRACT The Cox model is the recognized industry standard when designing and analyzing randomized clinical trials with right-censored data. As the model is based on the proportional hazards (PH) assumption, if the hazard ratio changes over time, as often occurs during long-term studies, the interpretation of the Cox hazard ratio becomes problematic. Furthermore, the Cox model is not powerful in the event of crossing hazards. Here, we consider a range of tests to compare two treatment groups in randomized clinical trials where the PH assumption is in doubt. The proposed methods are evaluated on simulated data and compared using data from a cancer clinical trial.