Blinded versus unblinded covariate selection in confirmatory survival Trials

• Verfasst von: Kunz, Christina [VerfasserIn]
• Verfasst von: Kieser, Meinhard [VerfasserIn]
• Titel: Blinded versus unblinded covariate selection in confirmatory survival Trials
• Verf.angabe: Christina Kunz and Meinhard Kieser
• E-Jahr: 2014
• Jahr: 07 Mar 2014
• Umfang: 17 S.
• Fussnoten: Gesehen am 10.08.2020
• Titel Quelle: Enthalten in: Journal of biopharmaceutical statistics
• Ort Quelle: Philadelphia, PA : Taylor & Francis, 1991
• Jahr Quelle: 2014
• Band/Heft Quelle: 24(2014), 2, Seite 398-414
• ISSN Quelle: 1520-5711
• DOI: doi:10.1080/10543406.2013.860158
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Adaptive design
• Sach-SW: Blinded data
• Sach-SW: Conditional rejection
• Sach-SW: Covariate selection
• Sach-SW: Left-truncation
• Sach-SW: Probability principle
• Sach-SW: Survival
• K10plus-PPN: 1726660850

Abstract

Adjustment for covariates and specification of the correct covariate set are important issues in the analysis of clinical trials. Edwards (1999) proposes a model selection approach where the model is chosen on the final data set, which remains blinded for treatment group allocation. We investigate this method for time-to-event endpoints and compare its performance to variable selection within an adaptive design. This adaptive design integrates the methods of Schäfer and Müller (2001) and Keiding et al. (1987) and allows variable selection on the unblinded data during an interim analysis. Monte Carlo simulation shows that Edwards’ method—though blinded—outperforms the adaptive method in terms of ability to select the survival relevant covariates and power. The application of the methods is illustrated by a clinical trial example.