Efficiency of Enrichment Design for Pre–Post Trials with Binary Endpoint
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Enrichment design is a common strategy in personalized medicine in which treatments are given only to patients who are tested positive on a genomic biomarker. Such a targeted trial, as compared to the untargeted trials in which all patients receive the treatments, can substantially reduce the sample size needed for a study as demonstrated in the literature for two-arm trials. To fill in the gaps in the existing literature, we consider trials to evaluate a targeted treatment by comparing pre–post trial outcomes to investigate the intervention effect after the treatment. We investigate the relative efficiency in terms of sample size reduction of an enrichment design against the conventional design, focusing on binary endpoints. The effects of misclassification of the genomic classifier on the relative efficiency are also investigated.
KeywordsEnrichment designs Genomic biomarkers Misclassification Personalized medicine Sample sizes and power Targeted treatment
The research was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the National Institutes of Health (NIH). The authors thank the Guest Editor-in-Chief and two referees for their helpful comments that improved the paper.
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