  The restricted mean survival time is a clinically easy-to-interpret measure
that does not require any assumption of proportional hazards. We focus on two
ways to directly model the survival time and adjust the covariates. One is to
calculate the pseudo-survival time for each subject using leave-one-out, and
then perform a model analysis using all pseudo-values to adjust for covariates.
The pseudo-survival time is used to reflect information of censored subjects in
the model analysis. The other method adjusts for covariates using subjects for
whom the time-to-event was observed while adjusting for the censored subjects
using the inverse probability of censoring weighting (IPCW). This paper
evaluates the performance of these two methods in terms of the power to detect
group differences through a simple example dataset and computer simulations.
The simple example illustrates the intuitive behavior of the two methods. With
the method using pseudo-survival times, it is difficult to interpret the
pseudo-values. We confirm that the pseudo-survival times are different from the
actual data obtained in a primary biliary cholangitis clinical trial because of
the many censored data. In the simulations, the method using IPCW is found to
be more powerful. Even in the case of group differences with respect to the
censor incidence rates and covariates, the method using IPCW maintains a
nominal significance level for the type-1 error rate. We conclude that the IPCW
method should be used to estimate the restricted mean survival time when
adjusting the covariates.
