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  • 3M-15SEP2015

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  • Jaki_et_al-2015-Statistics_in_Medicine

    Rights statement: © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Designing multi-arm multi-stage clinical trials using a risk-benefit criterion for treatment selection

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
<mark>Journal publication date</mark>20/02/2016
<mark>Journal</mark>Statistics in Medicine
Issue number4
Volume35
Number of pages12
Pages (from-to)522-533
Publication StatusPublished
Early online date12/10/15
<mark>Original language</mark>English

Abstract

Multi-arm clinical trials that compare several active treatments to a common control have been proposed as an efficient means of making an informed decision about which of several treatments should be evaluated further in a confirmatory study. Additional efficiency is gained by incorporating interim analyses and in particular, seamless Phase II/III designs have been the focus of recent research. Common to much of this work is the constraint that selection and formal testing should be based on a single efficacy endpoint, despite the fact that in practice, safety considerations will often play a central role in determining selection decisions. Here we develop a multi-arm multistage
design for a trial with an efficacy and safety endpoint. The safety endpoint is explicitly considered in the formulation of the problem, selection of experimental arm and hypothesis testing. The design extends group-sequential
ideas and considers the scenario where a minimal safety requirement is to be fulfilled and the treatment yielding the best combined safety and efficacy trade-off satisfying this constraint is selected for further testing. The treatment with the best trade-off is selected at the first interim analysis while the whole trial is allowed to comprise of J analyses. We show that the design controls the familywise error rate in the strong sense and illustrate the method through an example and simulation. We find that the design is robust to misspecification of the correlation between the endpoints and requires similar numbers of subjects to a trial based on efficacy alone for moderately correlated endpoints.

Bibliographic note

© 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.