PCN202 Use of Restricted Mean Survival Time in the Presence of Non-Proportional Hazards As an Alternative Measure of Treatment Benefit in Cost-Effectiveness Analyses

Abstract

The restricted mean survival time (rmst) is a well-established measure of treatment benefit, that is defined as the average event-free survival time up to a pre-specified time point. The rmst difference (rmstD) between two treatments corresponds to the area between their respective Kaplan Meier curves. This empirical study aimed to explore how to use the rmstD in cost-effectiveness models (CEM). The case study was based on a network of three studies related to lung cancer. Two analyses were conducted: the first considered the pooled Kaplan-Meier estimates (time horizon t* of 25 months) and the second was based on extrapolated mean survival time estimators (t* of 15 years). Distributions minimizing the Akaike Information Criteria were considered for the extrapolations of both the Progression-Free survival (Log-Logistic) and the Overall survival (Weibull), separately. The CEM was designed to allow for the use of the rmstD resulting from a random effect network meta-analysis (NMA). Discounted and undiscounted results were generated. The NMA estimates were highly sensitive to t*. The use of restricted or extrapolated estimates, with or without applying the discount rate led to similar conclusions in the cost-effectiveness assessments. The extrapolated mean survival time estimates allowed to capture all treatment benefit although it relied on a larger set of assumptions. This study demonstrates that the rmstD can be used to develop CEM in oncology, which provides a relevant method in a context of non-proportional hazards. The method is sensitive to the selection of the time horizon. Alternative computational methods of the rmstD need to be further explored to better understand the implications on the results. In practice, extrapolations should be based on real world evidence and expert opinions to better reflect expected long-term outcomes.