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Including historical data in the analysis of clinical trials: Is it worth the effort?
Data of previous trials with a similar setting are often available in the analysis of clinical trials. Several Bayesian methods have been proposed for including historical data as prior information in the analysis of the current trial, such as the (modified) power prior, the (robust) meta-analytic-p...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176344/ https://www.ncbi.nlm.nih.gov/pubmed/28322129 http://dx.doi.org/10.1177/0962280217694506 |
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author | van Rosmalen, Joost Dejardin, David van Norden, Yvette Löwenberg, Bob Lesaffre, Emmanuel |
author_facet | van Rosmalen, Joost Dejardin, David van Norden, Yvette Löwenberg, Bob Lesaffre, Emmanuel |
author_sort | van Rosmalen, Joost |
collection | PubMed |
description | Data of previous trials with a similar setting are often available in the analysis of clinical trials. Several Bayesian methods have been proposed for including historical data as prior information in the analysis of the current trial, such as the (modified) power prior, the (robust) meta-analytic-predictive prior, the commensurate prior and methods proposed by Pocock and Murray et al. We compared these methods and illustrated their use in a practical setting, including an assessment of the comparability of the current and the historical data. The motivating data set consists of randomised controlled trials for acute myeloid leukaemia. A simulation study was used to compare the methods in terms of bias, precision, power and type I error rate. Methods that estimate parameters for the between-trial heterogeneity generally offer the best trade-off of power, precision and type I error, with the meta-analytic-predictive prior being the most promising method. The results show that it can be feasible to include historical data in the analysis of clinical trials, if an appropriate method is used to estimate the heterogeneity between trials, and the historical data satisfy criteria for comparability. |
format | Online Article Text |
id | pubmed-6176344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-61763442018-10-15 Including historical data in the analysis of clinical trials: Is it worth the effort? van Rosmalen, Joost Dejardin, David van Norden, Yvette Löwenberg, Bob Lesaffre, Emmanuel Stat Methods Med Res Articles Data of previous trials with a similar setting are often available in the analysis of clinical trials. Several Bayesian methods have been proposed for including historical data as prior information in the analysis of the current trial, such as the (modified) power prior, the (robust) meta-analytic-predictive prior, the commensurate prior and methods proposed by Pocock and Murray et al. We compared these methods and illustrated their use in a practical setting, including an assessment of the comparability of the current and the historical data. The motivating data set consists of randomised controlled trials for acute myeloid leukaemia. A simulation study was used to compare the methods in terms of bias, precision, power and type I error rate. Methods that estimate parameters for the between-trial heterogeneity generally offer the best trade-off of power, precision and type I error, with the meta-analytic-predictive prior being the most promising method. The results show that it can be feasible to include historical data in the analysis of clinical trials, if an appropriate method is used to estimate the heterogeneity between trials, and the historical data satisfy criteria for comparability. SAGE Publications 2017-02-21 2018-10 /pmc/articles/PMC6176344/ /pubmed/28322129 http://dx.doi.org/10.1177/0962280217694506 Text en © The Author(s) 2017 http://creativecommons.org/licenses/by-nc/3.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Articles van Rosmalen, Joost Dejardin, David van Norden, Yvette Löwenberg, Bob Lesaffre, Emmanuel Including historical data in the analysis of clinical trials: Is it worth the effort? |
title | Including historical data in the analysis of clinical trials: Is it
worth the effort? |
title_full | Including historical data in the analysis of clinical trials: Is it
worth the effort? |
title_fullStr | Including historical data in the analysis of clinical trials: Is it
worth the effort? |
title_full_unstemmed | Including historical data in the analysis of clinical trials: Is it
worth the effort? |
title_short | Including historical data in the analysis of clinical trials: Is it
worth the effort? |
title_sort | including historical data in the analysis of clinical trials: is it
worth the effort? |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176344/ https://www.ncbi.nlm.nih.gov/pubmed/28322129 http://dx.doi.org/10.1177/0962280217694506 |
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