Kunz, Cornelia, Friede, Tim, Parsons, Nicholas R., Todd, Susan and Stallard, Nigel (2014) Data-driven treatment selection for seamless phase II/III trials incorporating early-outcome data. Pharmaceutical Statistics, Volume 13 (Number 4). pp. 238-246. doi:10.1002/pst.1619

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Abstract

Seamless phase II/III clinical trials are conducted in two stages with treatment selection at the first stage. In the first stage, patients are randomized to a control or one of k > 1 experimental treatments. At the end of this stage, interim data are analysed, and a decision is made concerning which experimental treatment should continue to the second stage. If the primary endpoint is observable only after some period of follow-up, at the interim analysis data may be available on some early outcome on a larger number of patients than those for whom the primary endpoint is available. These early endpoint data can thus be used for treatment selection. For two previously proposed approaches, the power has been shown to be greater for one or other method depending on the true treatment effects and correlations. We propose a new approach that builds on the previously proposed approaches and uses data available at the interim analysis to estimate these parameters and then, on the basis of these estimates, chooses the treatment selection method with the highest probability of correctly selecting the most effective treatment. This method is shown to perform well compared with the two previously described methods for a wide range of true parameter values. In most cases, the performance of the new method is either similar to or, in some cases, better than either of the two previously proposed methods. © 2014 The Authors. Pharmaceutical Statistics published by John Wiley & Sons Ltd.

Item Type:	Journal Article
Subjects:	Q Science > QR Microbiology
Divisions:	Faculty of Medicine > Warwick Medical School > Health Sciences > Statistics and Epidemiology Faculty of Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH):	Microtubules
Journal or Publication Title:	Pharmaceutical Statistics
Publisher:	John Wiley & Sons Ltd.
ISSN:	1539-1604
Official Date:	14 July 2014
Dates:	Date Event 14 July 2014 Published 2 May 2014 Available 30 March 2014 Accepted 19 April 2013 Submitted
Date of first compliant deposit:	28 December 2015
Volume:	Volume 13
Number:	Number 4
Number of Pages:	25
Page Range:	pp. 238-246
DOI:	10.1002/pst.1619
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	Cancer Research UK (CRUK)
Grant number:	C25425/A15182 (CRUK), C24461/A12772 (CRUK)

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