Optimal planning of phase II/III programs for clinical trials with multiple endpoints

• Verfasst von: Kieser, Meinhard [VerfasserIn]
• Verfasst von: Kirchner, Marietta [VerfasserIn]
• Verfasst von: Dölger, Eva [VerfasserIn]
• Verfasst von: Götte, Heiko [VerfasserIn]
• Titel: Optimal planning of phase II/III programs for clinical trials with multiple endpoints
• Verf.angabe: Meinhard Kieser, Marietta Kirchner, Eva Dölger, Heiko Götte
• E-Jahr: 2018
• Jahr: 26 April 2018
• Umfang: 21 S.
• Fussnoten: Gesehen am 21.10.2019
• Titel Quelle: Enthalten in: Pharmaceutical statistics
• Ort Quelle: New York, NY : Wiley, 2002
• Jahr Quelle: 2018
• Band/Heft Quelle: 17(2018), 5, Seite 437-457
• ISSN Quelle: 1539-1612
• DOI: doi:10.1002/pst.1861
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: drug development program
• Sach-SW: multiple endpoints
• Sach-SW: phase II/III
• Sach-SW: probability of success
• Sach-SW: sample size
• K10plus-PPN: 1679238140

Abstract

Owing to increased costs and competition pressure, drug development becomes more and more challenging. Therefore, there is a strong need for improving efficiency of clinical research by developing and applying methods for quantitative decision making. In this context, the integrated planning for phase II/III programs plays an important role as numerous quantities can be varied that are crucial for cost, benefit, and program success. Recently, a utility-based framework has been proposed for an optimal planning of phase II/III programs that puts the choice of decision boundaries and phase II sample sizes on a quantitative basis. However, this method is restricted to studies with a single time-to-event endpoint. We generalize this procedure to the setting of clinical trials with multiple endpoints and (asymptotically) normally distributed test statistics. Optimal phase II sample sizes and go/no-go decision rules are provided for both the “all-or-none” and “at-least-one” win criteria. Application of the proposed method is illustrated by drug development programs in the fields of Alzheimer disease and oncology.