Quantifying treatment differences in confirmatory trials under non-proportional hazards

TL;DR

This paper compares statistical methods for analyzing clinical trial data under non-proportional hazards, highlighting the interpretability and power of RMST-based tests versus traditional hazard ratio methods.

Contribution

It provides a comprehensive simulation study evaluating the performance of log-rank, weighted log-rank, and RMST tests under non-proportional hazards in oncology trials.

Findings

RMST ratio is interpretable regardless of proportional hazards.

RMST achieves similar power to the log-rank test.

Hazard ratio has limited interpretability under non-proportional hazards.

Abstract

Proportional hazards are a common assumption when designing confirmatory clinical trials in oncology. With the emergence of immunotherapy and novel targeted therapies, departure from the proportional hazard assumption is not rare in nowadays clinical research. Under non-proportional hazards, the hazard ratio does not have a straightforward clinical interpretation, and the log-rank test is no longer the most powerful statistical test even though it is still valid. Nevertheless, the log-rank test and the hazard ratio are still the primary analysis tools, and traditional approaches such as sample size increase are still proposed to account for the impact of non-proportional hazards. The weighed log-rank test and the test based on the restricted mean survival time (RMST) are receiving a lot of attention as a potential alternative to the log-rank test. We conduct a simulation study comparing the performance and operating characteristics of the log-rank test, the weighted log-rank test and the test based on the RMST, including a treatment effect estimation, under different non-proportional hazards patterns. Results show that, under non-proportional hazards, the hazard ratio and weighted hazard ratio have no straightforward clinical interpretation whereas the RMST ratio can be interpreted regardless of the proportional hazards assumption. In terms of power, the RMST achieves a similar performance when compared to the log-rank test.