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BioMed Research International
Volume 2015, Article ID 293564, 8 pages
http://dx.doi.org/10.1155/2015/293564
Research Article

The Power of Phase I Studies to Detect Clinical Relevant QTc Prolongation: A Resampling Simulation Study

1Statistik Georg Ferber GmbH, Cagliostrostrasse 14, 4125 Riehen, Switzerland
2Richmond Pharmacology Ltd., St George’s, University of London, Cranmer Terrace, London SW17 0RE, UK
3Cardiovascular and Cell Sciences Research Institute, St George’s, University of London, Cranmer Terrace, London SW17 0RE, UK

Received 20 March 2015; Revised 22 May 2015; Accepted 9 June 2015

Academic Editor: Giuseppe Biondi-Zoccai

Copyright © 2015 Georg Ferber et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Concentration-effect (CE) models applied to early clinical QT data from healthy subjects are described in the latest E14 Q&A document as promising analysis to characterise QTc prolongation. The challenges faced if one attempts to replace a TQT study by thorough ECG assessments in Phase I based on CE models are the assurance to obtain sufficient power and the establishment of a substitute for the positive control to show assay sensitivity providing protection against false negatives. To demonstrate that CE models in small studies can reliably predict the absence of an effect on QTc, we investigated the role of some key design features in the power of the analysis. Specifically, the form of the CE model, inclusion of subjects on placebo, and sparse sampling on the performance and power of this analysis were investigated. In this study, the simulations conducted by subsampling subjects from 3 different TQT studies showed that CE model with a treatment effect can be used to exclude small QTc effects. The number of placebo subjects was also shown to increase the power to detect an inactive drug preventing false positives while an effect can be underestimated if time points around are missed.