Sarah Donegan1, Paula Williamson1, Umberto D'Alessandro2, Catrin Tudur Smith1. 1. Department of Biostatistics, Faculty of Health & Life Sciences, University of Liverpool, Shelley's Cottage, Brownlow Street, Liverpool, L69 3GS, UK. 2. Department of Parasitology, Prince Leopold Institute of Tropical Medicine, National estraat 155, B-2000, Antwerp, Belgium.
Abstract
BACKGROUND: Homogeneity and consistency assumptions underlie network meta-analysis (NMA). Methods exist to assess the assumptions but they are rarely and poorly applied. We review and illustrate methods to assess homogeneity and consistency. METHODS: Eligible articles focussed on indirect comparison or NMA methodology. Articles were sought by hand-searching and scanning references (March 2013). Assumption assessment methods described in the articles were reviewed, and applied to compare anti-malarial drugs. RESULTS: 116 articles were included. Methods to assess homogeneity were: comparing characteristics across trials; comparing trial-specific treatment effects; using hypothesis tests or statistical measures; applying fixed-effect and random-effects pair-wise meta-analysis; and investigating treatment effect-modifiers. Methods to assess consistency were: comparing characteristics; investigating treatment effect-modifiers; comparing outcome measurements in the referent group; node-splitting; inconsistency modelling; hypothesis tests; back transformation; multidimensional scaling; a two-stage approach; and a graph-theoretical method. For the malaria example, heterogeneity existed for some comparisons that was unexplained by investigating treatment effect-modifiers. Inconsistency was detected using node-splitting and inconsistency modelling. It was unclear whether the covariates explained the inconsistency. CONCLUSIONS: Presently, we advocate applying existing assessment methods collectively to gain the best understanding possible regarding whether assumptions are reasonable. In our example, consistency was questionable; therefore the NMA results may be unreliable.
BACKGROUND: Homogeneity and consistency assumptions underlie network meta-analysis (NMA). Methods exist to assess the assumptions but they are rarely and poorly applied. We review and illustrate methods to assess homogeneity and consistency. METHODS: Eligible articles focussed on indirect comparison or NMA methodology. Articles were sought by hand-searching and scanning references (March 2013). Assumption assessment methods described in the articles were reviewed, and applied to compare anti-malarial drugs. RESULTS: 116 articles were included. Methods to assess homogeneity were: comparing characteristics across trials; comparing trial-specific treatment effects; using hypothesis tests or statistical measures; applying fixed-effect and random-effects pair-wise meta-analysis; and investigating treatment effect-modifiers. Methods to assess consistency were: comparing characteristics; investigating treatment effect-modifiers; comparing outcome measurements in the referent group; node-splitting; inconsistency modelling; hypothesis tests; back transformation; multidimensional scaling; a two-stage approach; and a graph-theoretical method. For the malaria example, heterogeneity existed for some comparisons that was unexplained by investigating treatment effect-modifiers. Inconsistency was detected using node-splitting and inconsistency modelling. It was unclear whether the covariates explained the inconsistency. CONCLUSIONS: Presently, we advocate applying existing assessment methods collectively to gain the best understanding possible regarding whether assumptions are reasonable. In our example, consistency was questionable; therefore the NMA results may be unreliable.
Authors: Brian Hutton; Mona Hersi; Wei Cheng; Misty Pratt; Pauline Barbeau; Sasha Mazzarello; Nadera Ahmadzai; Becky Skidmore; Scott C Morgan; Louise Bordeleau; Pamela K Ginex; Behnam Sadeghirad; Rebecca L Morgan; Katherine Marie Cole; Mark Clemons Journal: Oncol Nurs Forum Date: 2020-07-01 Impact factor: 2.172
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