multi_rmst: Test of RMST for comparing two or more survival curves

In MSCCT: Multiple Survival Crossing Curves Tests

Test of RMST for comparing two or more survival curves

Description

Performs the test of Restricted Mean Survival Time for two or more survival curves by comparing the difference of areas under survival curves.

Usage

multi_rmst(df, tau, method = p.adjust.methods, nboot = 500)

Arguments

df	A dataframe with columns : time : positive numbers, time-to-event; status : vector of integer, 0 or 1. 0 is (right) censoring, 1 is event; arm : a factor or object that can be coerced to one. The group the patient belongs to. Must have at least two levels.
tau	The truncation time, default is the lowest of the max(time) of the groups;
method	The correction used for the p-values. Must be in p.adjust.methods. Default is the Holm correction. Unused if number of groups equals two.
nboot	Number of bootstrap samples;

Details

For each group, the Restricted Mean Survival Time at time tau (RMST(tau)) is computed as the area under the survival curve between time 0 and tau. The test of RMST is a pairwise multiple comparison test. For each pair of groups, it tests whether the difference between the RMST(tau) is zero or not. If the difference is not null, then the survival curves cannot be equal.

For exactly two groups, a single test is performed. For more than two survival curves, it compares each survival curve to every other curves and tests the global null hypothesis "all curves are equal" against the hypothesis "the curves are not all equal".

Value

An object of class multi_rmst containing :

• rmst_mat RMST estimation for each arm;

• results A matrix. Each row represents a comparison of two curves and contains the difference of RMST, its standard deviation, the p-value and the adjusted p-value;

• p The p-value of the global test;

• nb_tests The number of performed tests;

• The parameters tau, method and nboot.

References

Royston, P., & Parmar, M. K. (2013). Restricted mean survival time: an alternative to the hazard ratio for the design and analysis of randomized trials with a time-to-event outcome. BMC medical research methodology, 13, 1-15.

Examples

  multi_rmst(data_under_PH, tau = 36, nboot = 300)
  multi_rmst(data_not_PH, tau = 36, method = "BH", nboot = 300)

MSCCT documentation built on Aug. 8, 2025, 6:26 p.m.