title: Biomarker informed add-arm design for unimodal response.
abstract: In this article, we propose a biomarker informed add-arm design for unimodal response. The new design contributes to optimizing the procedure of dose-finding when a biomarker of the study primary endpoint exists and prior evidence indicates a unimodal dose-response relationship. Designs with up to seven active treatment arms were considered. We propose the statistical approach for the Type I error control and carry out extensive simulation studies for the power performance of the design. The proposed design is shown to outperform the corresponding biomarker informed two-stage winner design in power on an average.
authors.affiliation: a Department of Biostatistics , Boston University , Boston , Massachusetts , USA.|b Biostatistics, Gilead Sciences, Inc ., Foster City , California , USA.
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.affiliation: a Department of Biostatistics , Boston University , Boston , Massachusetts , USA.|c Biometrics, AMAG Pharmaceuticals, Inc ., Lexington , Massachusetts , USA.
authors.forename: Mark
authors.initials: M
authors.lastname: Chang
authors.affiliation: a Department of Biostatistics , Boston University , Boston , Massachusetts , USA.|d Biostatistics, Pfizer, Inc ., Cambridge , Massachusetts , USA.
authors.forename: Sandeep
authors.initials: S
authors.lastname: Menon
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D023381:Endpoint Determination; D006801:Humans; D012107:Research Design; D018401:Sample Size
chemical_list: D015415:Biomarkers
keywords: Adaptive design; Type I error; biomarker; clinical trials; dose-finding; power