Power and Sample Size for Restricted Mean Survival Time Based Clinical Trials

Tools for Restricted Mean Survival Time based study design and analysis planning. Provides power and sample size calculations for two-arm studies using direct modeling approaches from the literature, including semiparametric additive models, linear Inverse Probability Weighting based models from Wei (2014) , multiplicative stratified models from Wang (2019) , and covariate-dependent censoring methods from Wang (2018) .

RMSTpowerBoost: Power and Sample Size Calculations for RMST-Based Trials

Overview

RMSTpowerBoost provides power and sample size tools for study designs that use restricted mean survival time (RMST) as a summary metric of time-to-event outcomes. The package supports covariate adjustment with analytical and simulation-based procedures for settings that include nonproportional hazards, stratification or multi-center effects, and dependent censoring.

The package includes both an R interface and a Shiny application for interactive use.

Key Features

• Linear IPCW-based RMST power and sample size calculations.
• Additive and multiplicative stratified models for multi-center or highly stratified studies.
• Bootstrap-based semiparametric GAM procedures for nonlinear covariate effects.
• Analytical and simulation-based methods for covariate-dependent censoring under a single censoring mechanism.

Installation

Install the development version from GitHub:

install.packages("remotes")
remotes::install_github("UTHSC-Zhang/RMSTpowerBoost-Package")

Shiny App

Interactive web application:

Launch the Shiny App