Advances in the GRADE approach to rate the certainty in estimates from a network meta-analysis
Author
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Brignardello Petersen, Romina
Author
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Bonner, Ashley
Author
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Alexander, Paul E.
Author
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Siemieniuk, Reed A. C.
Author
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Furukawa, Toshi A.
Author
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Rochwerg, Bram
Author
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Hazlewood, Glen S.
Author
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Alhazzani, Waleed
Author
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Mustafa, Reem A.
Author
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Murad, M. Hassan
Author
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Puhan, Milo A.
Author
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Schuenemann, Holger J.
Author
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Guyatt, Gordon H.
Admission date
dc.date.accessioned
2018-07-31T15:33:52Z
Available date
dc.date.available
2018-07-31T15:33:52Z
Publication date
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2018
Cita de ítem
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Journal of Clinical Epidemiology Volumen: 98 Páginas: 162-162
es_ES
Identifier
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10.1016/j.jclinepi.2018.04.013
Identifier
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https://repositorio.uchile.cl/handle/2250/150481
Abstract
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This article describes conceptual advances of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE)
working group guidance to evaluate the certainty of evidence (confidence in evidence, quality of evidence) from network meta-analysis
(NMA). Application of the original GRADE guidance, published in 2014, in a number of NMAs has resulted in advances that strengthen
its conceptual basis and make the process more efficient. This guidance will be useful for systematic review authors who aim to assess the
certainty of all pairwise comparisons from an NMA and who are familiar with the basic concepts of NMA and the traditional GRADE
approach for pairwise meta-analysis. Two principles of the original GRADE NMA guidance are that we need to rate the certainty of
the evidence for each pairwise comparison within a network separately and that in doing so we need to consider both the direct and indirect
evidence. We present, discuss, and illustrate four conceptual advances: (1) consideration of imprecision is not necessary when rating the
direct and indirect estimates to inform the rating of NMA estimates, (2) there is no need to rate the indirect evidence when the certainty of
the direct evidence is high and the contribution of the direct evidence to the network estimate is at least as great as that of the indirect
evidence, (3) we should not trust a statistical test of global incoherence of the network to assess incoherence at the pairwise comparison
level, and (4) in the presence of incoherence between direct and indirect evidence, the certainty of the evidence of each estimate can help
decide which estimate to believe. 2017 Elsevier Inc. All rights reserved.