Sample size calculation and blinded sample size recalculation in clinical trials where the treatment effect is measured by the relative risk

• Verfasst von: Pobiruchin, Monika [VerfasserIn]
• Verfasst von: Kieser, Meinhard [VerfasserIn]
• Titel: Sample size calculation and blinded sample size recalculation in clinical trials where the treatment effect is measured by the relative risk
• Verf.angabe: Monika Pobiruchin & Meinhard Kieser
• E-Jahr: 2013
• Jahr: 02 Jan 2013
• Umfang: 11 S.
• Fussnoten: Gesehen am 03.12.2021
• Titel Quelle: Enthalten in: Communications in statistics. Simulation and computation
• Ort Quelle: London : Taylor & Francis, 2001
• Jahr Quelle: 2013
• Band/Heft Quelle: 42(2013), 7, Seite 1643-1653
• ISSN Quelle: 1532-4141
• DOI: doi:10.1080/03610918.2012.674595
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: 62K99
• Sach-SW: 62P10
• Sach-SW: Adaptive design
• Sach-SW: Binomial distribution
• Sach-SW: Internal pilot study design
• Sach-SW: Relative risk
• Sach-SW: Sample size estimation
• Sach-SW: Sample size reestimation
• K10plus-PPN: 178017800X

Abstract

In clinical trials with binary endpoints, the required sample size does not depend only on the specified type I error rate, the desired power and the treatment effect but also on the overall event rate which, however, is usually uncertain. The internal pilot study design has been proposed to overcome this difficulty. Here, nuisance parameters required for sample size calculation are re-estimated during the ongoing trial and the sample size is recalculated accordingly. We performed extensive simulation studies to investigate the characteristics of the internal pilot study design for two-group superiority trials where the treatment effect is captured by the relative risk. As the performance of the sample size recalculation procedure crucially depends on the accuracy of the applied sample size formula, we firstly explored the precision of three approximate sample size formulae proposed in the literature for this situation. It turned out that the unequal variance asymptotic normal formula outperforms the other two, especially in case of unbalanced sample size allocation. Using this formula for sample size recalculation in the internal pilot study design assures that the desired power is achieved even if the overall rate is mis-specified in the planning phase. The maximum inflation of the type I error rate observed for the internal pilot study design is small and lies below the maximum excess that occurred for the fixed sample size design.