Abstract:
:An adaptive enrichment design is a randomized trial that allows enrollment criteria to be modified at interim analyses, based on a preset decision rule. When there is prior uncertainty regarding treatment effect heterogeneity, these trial designs can provide improved power for detecting treatment effects in subpopulations. We present a simulated annealing approach to search over the space of decision rules and other parameters for an adaptive enrichment design. The goal is to minimize the expected number enrolled or expected duration, while preserving the appropriate power and Type I error rate. We also explore the benefits of parallel computation in the context of this goal. We find that optimized designs can be substantially more efficient than simpler designs using Pocock or O'Brien-Fleming boundaries.
journal_name
J Biopharm Statjournal_title
Journal of biopharmaceutical statisticsauthors
Fisher A,Rosenblum M,Alzheimer’s Disease Neuroimaging Initiative.doi
10.1080/10543406.2018.1489401subject
Has Abstractpub_date
2018-01-01 00:00:00pages
966-982issue
5eissn
1054-3406issn
1520-5711journal_volume
28pub_type
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