  We conducted a systematic comparison of statistical methods used for the
analysis of time-to-event outcomes under various proportional and
nonproportional hazard (NPH) scenarios. Our study used data from recently
published oncology trials to compare the Log-rank test, still by far the most
widely used option, against some available alternatives, including the MaxCombo
test, the Restricted Mean Survival Time Difference (dRMST) test, the
Generalized Gamma Model (GGM) and the Generalized F Model (GFM). Power, type I
error rate, and time-dependent bias with respect to the RMST difference,
survival probability difference, and median survival time were used to evaluate
and compare the performance of these methods. In addition to the real data, we
simulated three hypothetical scenarios with crossing hazards chosen so that the
early and late effects 'cancel out' and used them to evaluate the ability of
the aforementioned methods to detect time-specific and overall treatment
effects. We implemented novel metrics for assessing the time-dependent bias in
treatment effect estimates to provide a more comprehensive evaluation in NPH
scenarios. Recommendations under each NPH scenario are provided by examining
the type I error rate, power, and time-dependent bias associated with each
statistical approach.
