Addressing between-study heterogeneity and inconsistency in mixed treatment comparisons: Application to stroke prevention treatments in individuals with non-rheumatic atrial fibrillation
Addressing between-study heterogeneity and inconsistency in mixed treatment comparisons: Application to stroke prevention treatments in individuals with non-rheumatic atrial fibrillation
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DOI：
10.1002/sim.3594
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发表时间：
2009-06-30
影响因子：
2
通讯作者：
Welton, Nicky J.
中科院分区：
文献类型：
--
作者：
Cooper, Nicola J.;Sutton, Alex J.;Welton, Nicky J.
混合治疗比较模型扩展了荟萃分析方法，以便在关注的临床领域的所有相关对照药物之间进行比较。在这种建模中，必须探索变异性的潜在来源，以解释异质性（成对对比内试验间治疗效果的变化）和不一致性（成对对比之间治疗效果的变化），以确保分析的有效性。本文的目的是扩展混合治疗比较框架，以纳入研究-水平协变量，试图解释研究间异质性并减少不一致性。三种可能的模型规格，假设不同的假设进行了描述和应用到一个17治疗网络中风预防治疗的个人与非风湿性atrial fibrillation.The论文证明了将协变量在一个混合的治疗比较框架，并使用模型拟合统计选择替代模型规格的可行性。尽管这种方法可以调整网络中的不一致性，但对于标准荟萃回归，如果试验数量与治疗对照药物数量相比较少，则分析的功效将较低。版权所有（C）2009约翰威利父子有限公司
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 in 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. Copyright (C) 2009 John Wiley & Sons, Ltd.