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Bayesian biomarker-driven outcome-adaptive randomization with an imperfect biomarker assay
Leandro Garcia Barrado1,2, Tomasz Burzykowski1,2,3
1I-BioStat, Hasselt University, Diepenbeek, Belgium.
Clinical Trials (London, England)
|November 24, 2020
Summary
Biomarker assay accuracy significantly impacts Bayesian adaptive randomization trial designs. Imperfect assays reduce power and increase type-I error, necessitating careful consideration before implementation.
Area of Science:
- Clinical Trial Design
- Biostatistics
- Biomarker Research
Background:
- Biomarker-driven adaptive randomization designs offer efficient clinical trial methodologies.
- The accuracy of biomarker assays is crucial for the reliable operation of these designs.
Purpose of the Study:
- To investigate the impact of biomarker assay accuracy on the operating characteristics of Bayesian biomarker-driven outcome-adaptive randomization designs.
- To quantify the effects of imperfect biomarker assays on trial power and type-I error rates.
Main Methods:
- A simulation study was conducted with two treatments and two biomarker strata.
- Four scenarios of underlying response probabilities were evaluated.
- The performance of perfect versus imperfect biomarker assays (sensitivity=0.8, specificity=0.7) was compared across different biomarker prevalence values.
Main Results:
- Imperfect biomarker assays significantly alter the operational characteristics of Bayesian adaptive randomization designs.
- Misclassification due to imperfect assays leads to a substantial reduction in statistical power.
- A considerable increase in type-I error probability was observed with imperfect biomarker assays.
Conclusions:
- The accuracy of biomarker assays is a critical factor in the success of Bayesian biomarker-driven outcome-adaptive randomization.
- The performance degradation necessitates careful evaluation of assay sensitivity, specificity, and biomarker prevalence before adopting such designs.
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