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Meta-analysis of randomized clinical trials in the era of individual patient data sharing

BACKGROUND: Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. METHODS: First, w...

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Autores principales: Kawahara, Takuya, Fukuda, Musashi, Oba, Koji, Sakamoto, Junichi, Buyse, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Japan 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5951901/
https://www.ncbi.nlm.nih.gov/pubmed/29330642
http://dx.doi.org/10.1007/s10147-018-1237-z
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author Kawahara, Takuya
Fukuda, Musashi
Oba, Koji
Sakamoto, Junichi
Buyse, Marc
author_facet Kawahara, Takuya
Fukuda, Musashi
Oba, Koji
Sakamoto, Junichi
Buyse, Marc
author_sort Kawahara, Takuya
collection PubMed
description BACKGROUND: Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. METHODS: First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. RESULTS: Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. CONCLUSIONS: Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future.
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spelling pubmed-59519012018-05-18 Meta-analysis of randomized clinical trials in the era of individual patient data sharing Kawahara, Takuya Fukuda, Musashi Oba, Koji Sakamoto, Junichi Buyse, Marc Int J Clin Oncol Special Article BACKGROUND: Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. METHODS: First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. RESULTS: Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. CONCLUSIONS: Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. Springer Japan 2018-01-12 2018 /pmc/articles/PMC5951901/ /pubmed/29330642 http://dx.doi.org/10.1007/s10147-018-1237-z Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Special Article
Kawahara, Takuya
Fukuda, Musashi
Oba, Koji
Sakamoto, Junichi
Buyse, Marc
Meta-analysis of randomized clinical trials in the era of individual patient data sharing
title Meta-analysis of randomized clinical trials in the era of individual patient data sharing
title_full Meta-analysis of randomized clinical trials in the era of individual patient data sharing
title_fullStr Meta-analysis of randomized clinical trials in the era of individual patient data sharing
title_full_unstemmed Meta-analysis of randomized clinical trials in the era of individual patient data sharing
title_short Meta-analysis of randomized clinical trials in the era of individual patient data sharing
title_sort meta-analysis of randomized clinical trials in the era of individual patient data sharing
topic Special Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5951901/
https://www.ncbi.nlm.nih.gov/pubmed/29330642
http://dx.doi.org/10.1007/s10147-018-1237-z
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