Introduction

gsDesign is a package for deriving and describing group sequentialdesigns. The package allows particular flexibility for designs withalpha- and beta-spending. Many plots are available for describing designproperties.

The gsDesign package supports group sequential clinical trial design.While there is a strong focus on designs using\(\alpha\)- and\(\beta\)-spending functions, Wang-Tsiatisdesigns, including O’Brien-Fleming and Pocock designs, are alsoavailable. The ability to design with non-binding futility rules allowscontrol of Type I error in a manner acceptable to regulatory authoritieswhen futility bounds are employed.

The routines are designed to provide simple access to commonly useddesigns using default arguments. Standard, published spending functionsare supported as well as the ability to write custom spending functions.AgsDesign class is defined and returned by thegsDesign() function. A plot function for this classprovides a wide variety of plots: boundaries, power, estimated treatmenteffect at boundaries, conditional power at boundaries, spending functionplots, expected sample size plot, and B-values at boundaries. Usingfunction calls to access the package routines provides a powerfulcapability to derive designs or output formatting that could not beanticipated through a GUI interface. This enables the user to easilycreate designs with features they desire, such as designs with minimumexpected sample size.

Thus, the intent of the gsDesign package is to easily create, fullycharacterize and even optimize routine group sequential trial designs aswell as provide a tool to evaluate innovative designs.

Example

Here is a minimal example assuming a fixed design (no interim) trialwith the same endpoint requires 200 subjects for 90% power at\(\alpha\) = 0.025, one-sided:

library(gsDesign)x<-gsDesign(n.fix =200)plot(x)

gsBoundSummary(x)#>   Analysis               Value Efficacy Futility#>  IA 1: 33%                   Z   3.0107  -0.2387#>      N: 72         p (1-sided)   0.0013   0.5943#>                ~delta at bound   1.5553  -0.1233#>            P(Cross) if delta=0   0.0013   0.4057#>            P(Cross) if delta=1   0.1412   0.0148#>  IA 2: 67%                   Z   2.5465   0.9411#>     N: 143         p (1-sided)   0.0054   0.1733#>                ~delta at bound   0.9302   0.3438#>            P(Cross) if delta=0   0.0062   0.8347#>            P(Cross) if delta=1   0.5815   0.0437#>      Final                   Z   1.9992   1.9992#>     N: 214         p (1-sided)   0.0228   0.0228#>                ~delta at bound   0.5963   0.5963#>            P(Cross) if delta=0   0.0233   0.9767#>            P(Cross) if delta=1   0.9000   0.1000

References