Methods for non-proportional hazards in clinical trials: A systematic review

TL;DR

This systematic review examines various statistical methods and software for analyzing time-to-event data under non-proportional hazards, addressing a gap in consensus and guidance for such approaches.

Contribution

It provides a comprehensive overview and unified notation of existing methods for non-proportional hazards in clinical trials, along with practical guidance.

Findings

Reviewed 211 relevant articles on NPH methods

Summarized effect measures, estimation, and testing approaches

Provided guidance and detailed explanations in supplementary material

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 (NPH) 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 NPH. 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 NPH situations. Using a unified notation, we provide an overview of methods available. Furthermore, we derive some guidance from the identified articles. We summarized the contents from the literature review in a concise way in the main text and provide more detailed explanations in the supplement.