GSDs are types of adaptive design that allow researchers to stop a trial early if they find compelling evidence that a treatment is effective or ineffective.
Suppose that we want to design a study to test whether a type of chemotherapy is effective for treating tumors and that we expect data to be collected over a few years’ time. Rather than performing one analysis once all the data have been collected, GSDs allow us to perform interim analyses as the data are collected. Each interim analysis provides the opportunity to stop the trial or continue collecting data. The trial can be stopped early if there is strong evidence of efficacy. The trial can also be stopped early if there is strong evidence of futility; this avoids exposing additional participants to an inadequate treatment.
Stata 18 offers a suite of commands for GSDs. The new gsbounds command calculates efficacy and futility bounds based on the number of analyses (also called looks), the desired overall Type I error, and the desired power. You can select from seven boundary-calculation methods—choose whether you want classical or error-spending methods and whether you want more conservative or less conservative bounds for early analyses. The new gsdesign command calculates efficacy and futility boundaries and provides sample sizes for the interim and final analyses for tests of means, proportions, and survivor functions.
Graphs make it easy to visualize the boundaries across all interim and final analyses.
The implementation of this feature within Stata is very user-friendly, the command syntax follows our straightforward syntax for power commands and results are easily accessible through the point-and-click interface. It is also powerful. Sample-size calculations can be extended beyond the tests of means, proportions, and survivor functions that are already available via gsdesign because users can specify a user-defined method.