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Optimal, minimax and admissible two-stage design for phase II oncology clinical trials

BACKGROUND: The article aims to compare the efficiency of minimax, optimal and admissible criteria in Simon’s and Fleming’s two-stage design. METHODS: Three parameter settings (p(1)-p(0) = 0.25–0.05, 0.30–0.10, 0.50–0.30) are designed to compare the maximum sample size, the critical values and the e...

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Autores principales: Qin, Fei, Wu, Jingwei, Chen, Feng, Wei, Yongyue, Zhao, Yang, Jiang, Zhiwei, Bai, Jianling, Yu, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7240995/
https://www.ncbi.nlm.nih.gov/pubmed/32434577
http://dx.doi.org/10.1186/s12874-020-01017-8
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author Qin, Fei
Wu, Jingwei
Chen, Feng
Wei, Yongyue
Zhao, Yang
Jiang, Zhiwei
Bai, Jianling
Yu, Hao
author_facet Qin, Fei
Wu, Jingwei
Chen, Feng
Wei, Yongyue
Zhao, Yang
Jiang, Zhiwei
Bai, Jianling
Yu, Hao
author_sort Qin, Fei
collection PubMed
description BACKGROUND: The article aims to compare the efficiency of minimax, optimal and admissible criteria in Simon’s and Fleming’s two-stage design. METHODS: Three parameter settings (p(1)-p(0) = 0.25–0.05, 0.30–0.10, 0.50–0.30) are designed to compare the maximum sample size, the critical values and the expected sample size for minimax, optimal and admissible designs. Type I & II error constraints (α, β) vary across (0.10, 0.10), (0.05, 0.20) and (0.05, 0.10), respectively. RESULTS: In both Simon’s and Fleming’s two-stage designs, the maximum sample size of admissible design is smaller than optimal design but larger than minimax design. Meanwhile, the expected samples size of admissible design is smaller than minimax design but larger than optimal design. Mostly, the maximum sample size and expected sample size in Fleming’s designs are considerably smaller than that of Simon’s designs. CONCLUSIONS: Whenever (p(0), p(1)) is pre-specified, it is better to explore in the range of probability q, based on relative importance between maximum sample size and expected sample size, and determine which design to choose. When q is unknown, optimal design may be more favorable for drugs with limited efficacy. Contrarily, minimax design is recommended if treatment demonstrates impressive efficacy.
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spelling pubmed-72409952020-05-29 Optimal, minimax and admissible two-stage design for phase II oncology clinical trials Qin, Fei Wu, Jingwei Chen, Feng Wei, Yongyue Zhao, Yang Jiang, Zhiwei Bai, Jianling Yu, Hao BMC Med Res Methodol Research Article BACKGROUND: The article aims to compare the efficiency of minimax, optimal and admissible criteria in Simon’s and Fleming’s two-stage design. METHODS: Three parameter settings (p(1)-p(0) = 0.25–0.05, 0.30–0.10, 0.50–0.30) are designed to compare the maximum sample size, the critical values and the expected sample size for minimax, optimal and admissible designs. Type I & II error constraints (α, β) vary across (0.10, 0.10), (0.05, 0.20) and (0.05, 0.10), respectively. RESULTS: In both Simon’s and Fleming’s two-stage designs, the maximum sample size of admissible design is smaller than optimal design but larger than minimax design. Meanwhile, the expected samples size of admissible design is smaller than minimax design but larger than optimal design. Mostly, the maximum sample size and expected sample size in Fleming’s designs are considerably smaller than that of Simon’s designs. CONCLUSIONS: Whenever (p(0), p(1)) is pre-specified, it is better to explore in the range of probability q, based on relative importance between maximum sample size and expected sample size, and determine which design to choose. When q is unknown, optimal design may be more favorable for drugs with limited efficacy. Contrarily, minimax design is recommended if treatment demonstrates impressive efficacy. BioMed Central 2020-05-20 /pmc/articles/PMC7240995/ /pubmed/32434577 http://dx.doi.org/10.1186/s12874-020-01017-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Qin, Fei
Wu, Jingwei
Chen, Feng
Wei, Yongyue
Zhao, Yang
Jiang, Zhiwei
Bai, Jianling
Yu, Hao
Optimal, minimax and admissible two-stage design for phase II oncology clinical trials
title Optimal, minimax and admissible two-stage design for phase II oncology clinical trials
title_full Optimal, minimax and admissible two-stage design for phase II oncology clinical trials
title_fullStr Optimal, minimax and admissible two-stage design for phase II oncology clinical trials
title_full_unstemmed Optimal, minimax and admissible two-stage design for phase II oncology clinical trials
title_short Optimal, minimax and admissible two-stage design for phase II oncology clinical trials
title_sort optimal, minimax and admissible two-stage design for phase ii oncology clinical trials
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7240995/
https://www.ncbi.nlm.nih.gov/pubmed/32434577
http://dx.doi.org/10.1186/s12874-020-01017-8
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