Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690
<p>Abstract</p> <p>Background</p> <p>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 o...
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| Format: | Article |
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BMC
2012-11-01
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| Series: | BMC Medical Research Methodology |
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| Online Access: | http://www.biomedcentral.com/1471-2288/12/183 |
| _version_ | 1818857110658613248 |
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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 | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Method</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>Such Bayesian analyses can be crucial in situations where the results from two theoretically identical trials yield somewhat conflicting or inconsistent results.</p> |
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| format | Article |
| id | doaj.art-3a3db679398b4246af083aa52317c23e |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-12-19T08:35:11Z |
| publishDate | 2012-11-01 |
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| spelling | doaj.art-3a3db679398b4246af083aa52317c23e2022-12-21T20:29:03ZengBMCBMC Medical Research Methodology1471-22882012-11-0112118310.1186/1471-2288-12-183Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690Ibrahim Joseph GChen Ming-HuiChu Haitao<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Method</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>Such Bayesian analyses can be crucial in situations where the results from two theoretically identical trials yield somewhat conflicting or inconsistent results.</p>http://www.biomedcentral.com/1471-2288/12/183Cure rate modelHistorical dataPrior distributionPosterior distribution |
| spellingShingle | Ibrahim Joseph G Chen Ming-Hui Chu Haitao Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690 BMC Medical Research Methodology Cure rate model Historical data Prior distribution Posterior distribution |
| 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 | Cure rate model Historical data Prior distribution Posterior distribution |
| url | http://www.biomedcentral.com/1471-2288/12/183 |
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