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タイトル: The Kilim plot: A tool for visualizing network meta-analysis results for multiple outcomes
著者: Seo, Michael
Furukawa, Toshiaki  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0003-2159-3776 (unconfirmed)
Veroniki, Areti Angeliki
Pillinger, Toby
Tomlinson, Anneka
Salanti, Georgia
Cipriani, Andrea
Efthimiou, Orestis
著者名の別形: 古川, 壽亮
キーワード: indirect comparisons
mixed evidence
multiple outcomes
multiple treatments meta-analysis
visualization
発行日: Jan-2021
出版者: Wiley
誌名: Research Synthesis Methods
巻: 12
号: 1
開始ページ: 86
終了ページ: 95
抄録: Network meta-analysis (NMA) can be used to compare multiple competing treatments for the same disease. In practice, usually a range of outcomes is of interest. As the number of outcomes increases, summarizing results from multiple NMAs becomes a nontrivial task, especially for larger networks. Moreover, NMAs provide results in terms of relative effect measures that can be difficult to interpret and apply in every-day clinical practice, such as the odds ratios. In this article, we aim to facilitate the clinical decision-making process by proposing a new graphical tool, the Kilim plot, for presenting results from NMA on multiple outcomes. Our plot compactly summarizes results on all treatments and all outcomes; it provides information regarding the strength of the statistical evidence of treatment effects, while it illustrates absolute, rather than relative, effects of interventions. Moreover, it can be easily modified to include considerations regarding clinically important effects. To showcase our method, we use data from a network of studies in antidepressants. All analyses are performed in R and we provide the source code needed to produce the Kilim plot, as well as an interactive web application.
著作権等: © 2020 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
URI: http://hdl.handle.net/2433/293479
DOI(出版社版): 10.1002/jrsm.1428
PubMed ID: 32524754
出現コレクション:学術雑誌掲載論文等

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