Sample size and effect size calculation for overall survival given the information on short-term binary endpoints.

In this work, we consider a mixture model that relates both the survival and binary endpoints. We distinguish between patients who respond to the binary endpoint, called responders, and those who don’t, non-responders. We use the difference of the restricted mean survival times (RMSTs) as the basis of the comparison between arms.

The expected effect size (RMSTs difference) and sample size are then calculated on the basis of the response rate of the binary endpoint as well as on the survival functions for responders and non-responders in each treatment arm.


This repository contains R functions for sample size and effect size calculation according to different set of parameters.

The functions included in this repository are the following:

  • survmixture_f to compute the survival distribution under the mixture model;
  • survm_effectsize to calculate the effect size (in terms of the RMST difference) according to the information on responders and non-responders;
  • survm_samplesize to calculate the sample size according to the distributional parameters of the responders and non-responders.

R Package

The R package survmixer is available on CRAN:

You can install the R package from CRAN:

# install.packages("survmixer")

or install the development version from GitHub:

# install.packages("devtools")

If you are a newcomer, you can take a look at the functions of the package using the vignettes:


This repository also contains the source files of the preprint:

  • “Design of phase III trials with long-term survival outcomes based on short-term binary results”. Marta Bofill Roig, Yu Shen, Guadalupe Gómez Melis. (2020).


  • In the folder CODE_paper/Example, there is the source code for reproduce the illustration;
  • In the folder CODE_paper/Simulations, there is the code to reproduce the simulation study in the paper;
  • In the folder CODE_paper/Additional-Simulations, there is the code to reproduce the simulation scenarios presented in the supplementary material;
  • Finally, in the folder CODE_paper/Sensitivity, there is the code to reproduce the simulation study to evaluate the performance of the sample size formula with respect to missepecifications in the model.