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    Rights statement: The final, definitive version of this article has been published in the Journal, Statistical Methods in Medical Research, 26 (4), 2017, © SAGE Publications Ltd, 2017 by SAGE Publications Ltd at the Statistical Methods in Medical Research page: http://journals.sagepub.com/home/smm on SAGE Journals Online: http://journals.sagepub.com/

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Two-stage phase II oncology designs using short-term endpoints for early stopping

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<mark>Journal publication date</mark>1/08/2017
<mark>Journal</mark>Statistical Methods in Medical Research
Issue number4
Volume26
Number of pages13
Pages (from-to)1671-1683
Publication StatusPublished
Early online date2/06/15
<mark>Original language</mark>English

Abstract

Phase II oncology trials are conducted to evaluate whether the tumour activity of a new treatment is promising enough to warrant further investigation. The most commonly used approach in this context is a two-stage single-arm design with binary endpoint. As for all designs with interim analysis, its efficiency strongly depends on the relation between recruitment rate and follow-up time required to measure the patients’ outcomes. Usually, recruitment is postponed after the sample size of the first stage is achieved up until the outcomes of all patients are available. This may lead to a considerable increase of the trial length and with it to a delay in the drug development process. We propose a design where an intermediate endpoint is used in the interim analysis to decide whether or not the study is continued with a second stage. Optimal and minimax versions of this design are derived. The characteristics of the proposed design in terms of type I error rate, power, maximum and expected sample size as well as trial duration are investigated. Guidance is given on how to select the most appropriate design. Application is illustrated by a phase II oncology trial in patients with advanced angiosarcoma, which motivated this research.

Bibliographic note

The final, definitive version of this article has been published in the Journal, Statistical Methods in Medical Research, 26 (4), 2017, © SAGE Publications Ltd, 2017 by SAGE Publications Ltd at the Statistical Methods in Medical Research page: http://journals.sagepub.com/home/smm on SAGE Journals Online: http://journals.sagepub.com/