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Design of randomized clinical trials with a binary endpoint: Conditional versus unconditional analyses of a
Edward L Korn1, Boris Freidlin1
1Biometric Research Program, National Cancer Institute, Bethesda, Maryland, USA.
Statistics in Medicine
|May 23, 2024
Summary
Unconditional exact tests, like Boschloo's, are more powerful than Fisher's exact test for randomized clinical trials with binary outcomes. This leads to smaller sample sizes, making them preferable for clinical trial design.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Statistical Inference
Background:
- Sample size determination for randomized clinical trials (RCTs) with binary endpoints relies heavily on the chosen hypothesis testing procedure.
- Fisher's exact test, a common method for 2x2 tables, offers a type 1 error rate less than or equal to the nominal level when analyzed conditionally.
- Unconditional exact tests also preserve type 1 error but are generally less conservative and more powerful than Fisher's exact test.
Purpose of the Study:
- To critically evaluate the statistical arguments favoring conditional analysis with Fisher's exact test in RCTs.
- To highlight the sample-size benefits of using unconditional exact tests, such as Boschloo's test, in clinical trial design.
- To explore the potential for further power enhancement in unconditional tests using pre-specified response rates.
Main Methods:
- Review of statistical arguments for conditional analysis of 2x2 tables in the context of RCTs.
- Comparison of the power and type 1 error characteristics of Fisher's exact test versus unconditional exact tests (e.g., Boschloo's test).
- Exploration of the implications of using target null and alternative response rates to improve unconditional test power.
Main Results:
- Arguments for conditional analysis of 2x2 tables in RCTs were found to be largely irrelevant or unconvincing in this specific context.
- Unconditional exact tests, particularly Boschloo's test, demonstrate superior power compared to Fisher's exact test, enabling smaller clinical trial sample sizes.
- The potential exists to enhance the power of unconditional tests by incorporating prior knowledge of null and alternative response rates.
Conclusions:
- The sample-size advantages of unconditional exact tests warrant their recommended use in the design of randomized clinical trials with binary endpoints.
- Statistical justifications for exclusively using conditional Fisher's exact test in RCTs are weak, especially when sample size reduction is a priority.
- Future research should focus on leveraging target response rates to optimize the power of unconditional exact tests for more efficient clinical trial design.
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