Point estimation in adaptive enrichment designs

• Verfasst von: Kunzmann, Kevin [VerfasserIn]
• Verfasst von: Benner, Laura [VerfasserIn]
• Verfasst von: Kieser, Meinhard [VerfasserIn]
• Titel: Point estimation in adaptive enrichment designs
• Verf.angabe: Kevin Kunzmann, Laura Benner, Meinhard Kieser
• E-Jahr: 2017
• Jahr: 10 November 2017
• Umfang: 13 S.
• Fussnoten: Gesehen am 05.11.2018
• Titel Quelle: Enthalten in: Statistics in medicine
• Ort Quelle: Chichester [u.a.] : Wiley, 1982
• Jahr Quelle: 2017
• Band/Heft Quelle: 36(2017), 25, Seite 3935-3947
• ISSN Quelle: 1097-0258
• DOI: doi:10.1002/sim.7412
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: bias reduction
• Sach-SW: enrichment designs
• Sach-SW: point estimation
• Sach-SW: subgroup selection
• K10plus-PPN: 1582568596

Abstract

Adaptive enrichment designs are an attractive option for clinical trials that aim at demonstrating efficacy of therapies, which may show different benefit for the full patient population and a prespecified subgroup. In these designs, based on interim data, either the subgroup or the full population is selected for further exploration. When selection is based on efficacy data, this introduces bias to the commonly used maximum likelihood estimator. For the situation of two-stage designs with a single prespecified subgroup, we present six alternative estimators and investigate their performance in a simulation study. The most consistent reduction of bias over the range of scenarios considered was achieved by a method combining the uniformly minimum variance conditionally unbiased estimator with a conditional moment estimator. Application of the methods is illustrated by a clinical trial example.