- Abstract:
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It is often challenging to present the available evidence in a timely and comprehensible manner. We aimed to visualize the evolution of evidence about antidepressants for depression by conducting cumulative network meta‐analyses (NMAs) and to examine whether it could have helped the selection of optimal drugs. We built a Shiny web application that performs and presents cumulative NMAs based on R netmeta. We used a comprehensive dataset of double‐blind randomized controlled trials of 21 antide...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Publisher copy:
- 10.1002/jrsm.1413
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- Publisher:
- Wiley Publisher's website
- Journal:
- Research Synthesis Methods Journal website
- Publication date:
- 2020-05-25
- Acceptance date:
- 2020-04-21
- DOI:
- EISSN:
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1759-2887
- ISSN:
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1759-2879
- Pubs id:
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1101138
- Local pid:
- pubs:1101138
- Language:
- English
- Keywords:
- Copyright holder:
- Luo et al.
- Copyright date:
- 2020
- Rights statement:
- © 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‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
Journal article
Visualizing the evolution of evidence: Cumulative network meta‐analyses of new generation antidepressants in the last 40 years
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