Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes

Two-stage designs are commonly used for Phase II trials. Optimal two-stage designs have the lowest expected sample size for a specific treatment effect, for example, the null value, but can perform poorly if the true treatment effect differs. Here we introduce a design for continuous treatment respo...

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Main Authors:	Wason, James M. S., Mander, Adrian P.
Format:	Online
Language:	English
Published:	Taylor & Francis 2012
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3662082/

id	pubmed-3662082
recordtype	oai_dc
spelling	pubmed-36620822013-05-28 Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes Wason, James M. S. Mander, Adrian P. Research Article Two-stage designs are commonly used for Phase II trials. Optimal two-stage designs have the lowest expected sample size for a specific treatment effect, for example, the null value, but can perform poorly if the true treatment effect differs. Here we introduce a design for continuous treatment responses that minimizes the maximum expected sample size across all possible treatment effects. The proposed design performs well for a wider range of treatment effects and so is useful for Phase II trials. We compare the design to a previously used optimal design and show it has superior expected sample size properties. Taylor & Francis 2012-05-31 2012-07 /pmc/articles/PMC3662082/ /pubmed/22651118 http://dx.doi.org/10.1080/10543406.2010.528104 Text en Copyright © Taylor & Francis Group, LLC http://www.informaworld.com/mpp/uploads/iopenaccess_tcs.pdf This is an open access article distributed under the Supplemental Terms and Conditions for iOpenAccess articles published in Taylor & Francis journals (http://www.informaworld.com/mpp/uploads/iopenaccess_tcs.pdf) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Wason, James M. S. Mander, Adrian P.
spellingShingle	Wason, James M. S. Mander, Adrian P. Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes
author_facet	Wason, James M. S. Mander, Adrian P.
author_sort	Wason, James M. S.
title	Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes
title_short	Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes
title_full	Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes
title_fullStr	Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes
title_full_unstemmed	Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes
title_sort	minimizing the maximum expected sample size in two-stage phase ii clinical trials with continuous outcomes
description	Two-stage designs are commonly used for Phase II trials. Optimal two-stage designs have the lowest expected sample size for a specific treatment effect, for example, the null value, but can perform poorly if the true treatment effect differs. Here we introduce a design for continuous treatment responses that minimizes the maximum expected sample size across all possible treatment effects. The proposed design performs well for a wider range of treatment effects and so is useful for Phase II trials. We compare the design to a previously used optimal design and show it has superior expected sample size properties.
publisher	Taylor & Francis
publishDate	2012
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3662082/
_version_	1611980445604380672

Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes

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