Optimal planning of adaptive two-stage designs

• Verfasst von: Pilz, Maximilian [VerfasserIn]
• Verfasst von: Kunzmann, Kevin [VerfasserIn]
• Verfasst von: Herrmann, Carolin [VerfasserIn]
• Verfasst von: Rauch, Geraldine [VerfasserIn]
• Verfasst von: Kieser, Meinhard [VerfasserIn]
• Titel: Optimal planning of adaptive two-stage designs
• Verf.angabe: Maximilian Pilz, Kevin Kunzmann, Carolin Herrmann, Geraldine Rauch, Meinhard Kieser
• Jahr: 2021
• Umfang: 18 S.
• Fussnoten: Gesehen am 17.04.2023
• Titel Quelle: Enthalten in: Statistics in medicine
• Ort Quelle: Chichester [u.a.] : Wiley, 1982
• Jahr Quelle: 2021
• Band/Heft Quelle: 40(2021), 13, Seite 3196-3213
• ISSN Quelle: 1097-0258
• DOI: doi:10.1002/sim.8953
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: adaptive design
• Sach-SW: clinical trial
• Sach-SW: optimal design
• Sach-SW: sample size calculation
• K10plus-PPN: 1842819399
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

Adaptive designs are playing an increasingly important role in the planning of clinical trials. While there exists various research on the optimal determination of a two-stage design, non-optimal versions still are frequently applied in clinical research. In this article, we strive to motivate the application of optimal adaptive designs and give guidance on how to determine them. It is demonstrated that optimizing a trial design with respect to particular objective criteria can have a substantial benefit over the application of conventional adaptive sample size recalculation rules. Furthermore, we show that in many practical situations, optimal group-sequential designs show an almost negligible performance loss compared to optimal adaptive designs. Finally, we illustrate how optimal designs can be tailored to specific operational requirements by customizing the underlying optimization problem.