R for HTA 2022 Workshop - Lytske Bakker
Channel: R-HTA consortium
Date: 2022-06-01

Lytske Bakker

Title:
Estimating Restricted Mean Survival Time

Abstract:
In recent years, there has been an increasing interest in using restricted mean survival time (RMST) as an alternative to the hazard ratio for assessing treatment effectiveness. Common challenges with the hazard ratio are its limited value when the proportional hazards assumption does not hold and the lack of clinical meaning. In addition to its use for assessing treatment effectiveness, the RMST can be useful to gain insight into the differences between extrapolated survival curves for cost-effectiveness analyses.

The flexsurv package allows an easy estimation of restricted mean survival time after having extrapolated the different survival curves. The type  = "rmst" argument within the summary() function enables the user to present results in terms of the restricted mean survival time including the lower and upper confidence intervals. There are several other packages that allow users to estimate restricted mean survival such as the RISCA and survRM2 packages which appear to have a slightly different purpose. Where the flexsurv package calculates the (flexible) parametric model dependent RMST the RISCA package calculates the area under the curve using the simpler trapezoidal rule.

In this session I would like to initiate the discussion as to whether alternatives to estimate RMST are available and when their use is recommended. First, I would like to present the code that I use when comparing RMST of extrapolated survival curves based on the flexsurv package. Hereafter, I would like to discuss with those present if and when alternative options can be considered.