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Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690
BACKGROUND: E1684 was the pivotal adjuvant melanoma trial for establishment of high-dose interferon (IFN) as effective therapy of high-risk melanoma patients. E1690 was an intriguing effort to corroborate E1684, and the differences between the outcomes of these trials have embroiled the field in con...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571975/ https://www.ncbi.nlm.nih.gov/pubmed/23194570 http://dx.doi.org/10.1186/1471-2288-12-183 |
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author | Ibrahim, Joseph G Chen, Ming-Hui Chu, Haitao |
author_facet | Ibrahim, Joseph G Chen, Ming-Hui Chu, Haitao |
author_sort | Ibrahim, Joseph G |
collection | PubMed |
description | BACKGROUND: E1684 was the pivotal adjuvant melanoma trial for establishment of high-dose interferon (IFN) as effective therapy of high-risk melanoma patients. E1690 was an intriguing effort to corroborate E1684, and the differences between the outcomes of these trials have embroiled the field in controversy over the past several years. The analyses of E1684 and E1690 were carried out separately when the results were published, and there were no further analyses trying to perform a single analysis of the combined trials. METHOD: In this paper, we consider such a joint analysis by carrying out a Bayesian analysis of these two trials, thus providing us with a consistent and coherent methodology for combining the results from these two trials. RESULTS: The Bayesian analysis using power priors provided a more coherent flexible and potentially more accurate analysis than a separate analysis of these data or a frequentist analysis of these data. The methodology provides a consistent framework for carrying out a single unified analysis by combining data from two or more studies. CONCLUSIONS: Such Bayesian analyses can be crucial in situations where the results from two theoretically identical trials yield somewhat conflicting or inconsistent results. |
format | Online Article Text |
id | pubmed-3571975 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35719752013-02-20 Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690 Ibrahim, Joseph G Chen, Ming-Hui Chu, Haitao BMC Med Res Methodol Research Article BACKGROUND: E1684 was the pivotal adjuvant melanoma trial for establishment of high-dose interferon (IFN) as effective therapy of high-risk melanoma patients. E1690 was an intriguing effort to corroborate E1684, and the differences between the outcomes of these trials have embroiled the field in controversy over the past several years. The analyses of E1684 and E1690 were carried out separately when the results were published, and there were no further analyses trying to perform a single analysis of the combined trials. METHOD: In this paper, we consider such a joint analysis by carrying out a Bayesian analysis of these two trials, thus providing us with a consistent and coherent methodology for combining the results from these two trials. RESULTS: The Bayesian analysis using power priors provided a more coherent flexible and potentially more accurate analysis than a separate analysis of these data or a frequentist analysis of these data. The methodology provides a consistent framework for carrying out a single unified analysis by combining data from two or more studies. CONCLUSIONS: Such Bayesian analyses can be crucial in situations where the results from two theoretically identical trials yield somewhat conflicting or inconsistent results. BioMed Central 2012-11-29 /pmc/articles/PMC3571975/ /pubmed/23194570 http://dx.doi.org/10.1186/1471-2288-12-183 Text en Copyright ©2012 Ibrahim et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ibrahim, Joseph G Chen, Ming-Hui Chu, Haitao Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690 |
title | Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690 |
title_full | Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690 |
title_fullStr | Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690 |
title_full_unstemmed | Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690 |
title_short | Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690 |
title_sort | bayesian methods in clinical trials: a bayesian analysis of ecog trials e1684 and e1690 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571975/ https://www.ncbi.nlm.nih.gov/pubmed/23194570 http://dx.doi.org/10.1186/1471-2288-12-183 |
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