Combining individual patient data and aggregate data in mixed treatment comparison meta-analysis: Individual patient data may be beneficial if only for a subset of trials
Combining individual patient data and aggregate data in mixed treatment comparison meta-analysis: Individual patient data may be beneficial if only for a subset of trials
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DOI：
10.1002/sim.5584
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发表时间：
2013-03-15
影响因子：
2
通讯作者：
Smith, Catrin Tudur
中科院分区：
文献类型：
--
作者：
Donegan, Sarah;Williamson, Paula;Smith, Catrin Tudur
个体患者数据（IPD）荟萃分析是金标准。当无法获得所有相关研究的IPD时，可以使用传统的成对荟萃分析合并汇总数据（AD）和IPD。我们将该方法扩展到联合收割机IPD和AD的混合治疗比较（MTC）荟萃分析。方法提出的随机效应MTC模型结合联合收割机IPD和AD的二分结果。我们通过在模型中纳入治疗与协变量的相互作用来评估潜在一致性假设时，研究了获得IPD对一部分试验的益处。我们描述了三种不同的模型规范，使越来越强的假设的相互作用。我们通过应用于真实的数据集来说明该方法，通过使用第28天的结果未调整的治疗成功来比较治疗疟疾的药物。我们比较了单独AD、单独IPD和所有数据的结果。结果当IPD贡献时（即单独使用IPD或将IPD和AD组合使用），链收敛，并且我们确定了相互作用的统计学显著回归系数。单独使用IPD，我们只能比较六种治疗方法中的三种。当模型拟合AD时，相互作用的处理效应和回归系数更加不精确，并且链不收敛。结论IPD和AD联合模型包含了所有可用的证据。在探索相互作用时，获得试验子集的IPD并将联合收割机IPD与其他AD结合可能是有益的。版权所有（c）2012约翰威利父子有限公司
Background Individual patient data (IPD) meta-analysis is the gold standard. Aggregate data (AD) and IPD can be combined using conventional pairwise meta-analysis when IPD cannot be obtained for all relevant studies. We extend the methodology to combine IPD and AD in a mixed treatment comparison (MTC) meta-analysis. Methods The proposed random-effects MTC models combine IPD and AD for a dichotomous outcome. We study the benefits of acquiring IPD for a subset of trials when assessing the underlying consistency assumption by including treatment-by-covariate interactions in the model. We describe three different model specifications that make increasingly stronger assumptions regarding the interactions. We illustrate the methodology through application to real data sets to compare drugs for treating malaria by using the outcome unadjusted treatment success at day 28. We compare results from AD alone, IPD alone and all data. Results When IPD contributed (i.e. either using IPD alone or combining IPD and AD), the chains converged, and we identified statistically significant regression coefficients for the interactions. Using IPD alone, we were able to compare only three of the six treatments of interest. When models were fitted to AD, the treatment effects and regression coefficients for the interactions were far more imprecise, and the chains did not converge. Conclusions The models combining IPD and AD encapsulated all available evidence. When exploring interactions, it can be beneficial to obtain IPD for a subset of trials and to combine IPD with additional AD. Copyright (c) 2012 John Wiley & Sons, Ltd.