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Flexible stopping boundaries when changing primary endpoints after unblinded interim analyses.
Liddy M Chen1, Joseph G Ibrahim, Haitao Chu
1a Global Research Operation, Biostatistics, PAREXEL International , Durham , North Carolina , USA.
Journal of Biopharmaceutical Statistics
|April 5, 2014
Summary
Clinical trials face inflated type I error with interim analyses. This study extends alpha spending functions for group sequential designs with preplanned endpoint switching, controlling overall error rates.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Statistical Methods
Background:
- Interim analyses in clinical trials can increase the risk of type I errors.
- Existing methods like group sequential boundaries and alpha spending functions control type I error for consistent endpoints.
Purpose of the Study:
- To extend alpha spending functions for group sequential designs.
- To accommodate preplanned endpoint switching after unblinded interim analyses.
- To develop group sequential stopping boundaries for analyses with potentially different parameters.
Main Methods:
- Extension of the alpha spending function methodology.
- Application to group sequential designs with preplanned endpoint switching.
- Development of stopping boundaries for interim and final analyses with varying parameters.
Main Results:
- The extended alpha spending function method provides a framework for controlling type I error in group sequential trials with endpoint switching.
- This approach allows for flexible adjustments to stopping boundaries when parameters differ across analyses.
Conclusions:
- The proposed method effectively controls the overall type I error rate in group sequential designs incorporating preplanned endpoint switching.
- This offers a statistically sound approach for complex clinical trial designs with interim analyses and changing endpoints.
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