Methods for non-proportional hazards in clinical trials: A systematic review
Maximilian Bardo, Cynthia Huber, Norbert Benda, Jonas Brugger, Tobias Fellinger, Vaidotas Galaunė, Judith Heinz, Harald Heinzl, Andrew C. Hooker, Florian Klinglmüller, Franz König, Tim Mathes, Martina Mittlböck, Martin Posch, Robin Ristl, Tim Friede
Abstract
For the analysis of time-to-event data, frequently used methods such as the log-rank test or the Cox proportional hazards model are based on the proportional hazards assumption, which is often debatable. Although a wide range of parametric and non-parametric methods for non-proportional hazards has been proposed, there is no consensus on the best approaches. To close this gap, we conducted a systematic literature search to identify statistical methods and software appropriate under non-proportional hazard. Our literature search identified 907 abstracts, out of which we included 211 articles, mostly methodological ones. Review articles and applications were less frequently identified. The articles discuss effect measures, effect estimation and regression approaches, hypothesis tests, and sample size calculation approaches, which are often tailored to specific non-proportional hazard situations. Using a unified notation, we provide an overview of methods available. Furthermore, we derive some guidance from the identified articles.