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A combined score test for binary and ordinal endpoints from clinical trials
John Whitehead1, Michael Branson, Susan Todd
1Department of Mathematics and Statistics, Lancaster University, Lancaster, UK. j.whitehead@lancaster.ac.uk
Statistics in Medicine
|January 19, 2010
Summary
This study presents a direct method for combining multiple endpoints in clinical trials, enhancing statistical power for experimental treatments. The approach validates combined score tests and aids in sample size calculations for sequential designs.
Area of Science:
- Clinical Trials Methodology
- Biostatistics
- Medical Research
Background:
- Increasing interest in combining multiple endpoints for evaluating experimental treatments, particularly in stroke research.
- Endpoints may involve repeated measures or different scales, often binary or ordinal.
Purpose of the Study:
- To develop a direct statistical approach for combining univariate score statistics across multiple endpoints.
- To derive correlations between score statistics for valid combined score testing.
- To provide a sample size formula and discuss sequential design applications.
Main Methods:
- Direct combination of univariate score statistics for each endpoint.
- Derivation of correlations between score statistics.
- Application in illustrative analyses and simulations, compared with generalized estimating equations.
Main Results:
- A valid combined score test is developed by accounting for correlations between endpoint score statistics.
- A sample size formula is deduced for studies with multiple endpoints.
- The proposed method demonstrates advantages and disadvantages compared to generalized estimating equations.
Conclusions:
- The direct approach offers a statistically sound method for combining multiple endpoints in clinical trial evaluations.
- This method enhances the analysis of experimental treatments by integrating diverse outcome measures.
- The findings support improved trial design and sample size determination for complex endpoint structures.
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