Meta-analysis and network meta-analysis of time-to-event outcomes with non-proportional hazards: a Bayesian time-varying hazard ratio approach
Rhiannon K Owen, Keith R Abrams

TL;DR
This paper introduces a Bayesian time-varying hazard ratio approach for meta-analyzing time-to-event outcomes with non-proportional hazards, enhancing interpretability and usability in health technology assessments.
Contribution
It proposes a novel Bayesian method to estimate time-varying hazard ratios in meta-analyses, addressing non-proportional hazards issues more effectively.
Findings
The approach revealed non-proportional hazards in gastric cancer and melanoma studies.
Time-varying HRs provided more nuanced insights into treatment effects over time.
Method demonstrated consistent superiority of certain treatments from specific time points.
Abstract
Background: Often when undertaking meta-analyses of time-to-event (TTE) outcomes, especially in a Health Technology Assessment context, a hazard ratio (HR) scale is used. However, issues arise when there is evidence of non-proportional hazards in some of the studies included. A number of methods have been advocated, but their use has been limited by either their complexity and/or the ease with which their results can be used in HTA. An alternative approach is to assume a treatment-log(time) interaction within a Cox proportional hazards model for each study, and to then undertake a bivariate meta-analysis of the resulting treatment and interaction coefficients, so that an overall time-varying HR (TVHR) can be obtained. Methods: A TVHR approach was applied to a meta-analysis of chemotherapy compared to Standard of Care for advanced recurrent gastric cancer, and in which Progression-Free…
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