Please use this identifier to cite or link to this item:
Title: Addressing between-study heterogeneity and inconsistency in mixed treatment comparisons: Application to stroke prevention treatments in individuals with non-rheumatic atrial fibrillation.
Authors: Cooper, NJ
Sutton, AJ
Morris, D
Ades, AE
Welton, NJ
First Published: 30-Jun-2009
Citation: STAT MED, 2009, 28 (14), pp. 1861-1881
Abstract: Mixed treatment comparison models extend meta-analysis methods to enable comparisons to be made between all relevant comparators in the clinical area of interest. In such modelling it is imperative that potential sources of variability are explored to explain both heterogeneity (variation in treatment effects between trials within pairwise contrasts) and inconsistency (variation in treatment effects between pairwise contrasts) to ensure the validity of the analysis.The objective of this paper is to extend the mixed treatment comparison framework to allow for the incorporation of study-level covariates in an attempt to explain between-study heterogeneity and reduce inconsistency. Three possible model specifications assuming different assumptions are described and applied to a 17-treatment network for stroke prevention treatments in individuals with non-rheumatic atrial fibrillation.The paper demonstrates the feasibility of incorporating covariates within a mixed treatment comparison framework and using model fit statistics to choose between alternative model specifications. Although such an approach may adjust for inconsistencies in networks, as for standard meta-regression, the analysis will suffer from low power if the number of trials is small compared with the number of treatment comparators.
DOI Link: 10.1002/sim.3594
eISSN: 1097-0258
Type: Journal Article
Appears in Collections:Published Articles, Dept. of Health Sciences

Files in This Item:
There are no files associated with this item.

Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.