BACKGROUND Network meta-analysis (NMA) is becoming increasingly popular in systematic reviews and health technology assessments. However, there is still ambiguity concerning the properties of the estimation approaches as well as for the methods to evaluate the consistency assumption. METHODS We conducted a simulation study for networks with up to 5 interventions. We investigated the properties of different methods and give recommendations for practical application. We evaluated the performance of 3 different models for complex networks as well as corresponding global methods to evaluate the consistency assumption. The models are the frequentist graph-theoretical approach netmeta, the Bayesian mixed treatment comparisons (MTC) consistency model, and the MTC consistency model with stepwise removal of studies contributing to inconsistency identified in a leverage plot. RESULTS We found that with a high degree of inconsistency none of the evaluated effect estimators produced reliable results, whereas with moderate or no inconsistency the estimator from the MTC consistency model and the netmeta estimator showed acceptable properties. We also saw a dependency on the amount of heterogeneity. Concerning the evaluated methods to evaluate the consistency assumption, none was shown to be suitable. CONCLUSIONS Based on our results we recommend a pragmatic approach for practical application in NMA. The estimator from the netmeta approach or the estimator from the Bayesian MTC consistency model should be preferred. Since none of the methods to evaluate the consistency assumption showed satisfactory results, users should have a strong focus on the similarity as well as the homogeneity assumption.

中文翻译：

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仿真研究比较了网络元分析的不同估计方法和评估一致性假设的相应方法。

背景技术网络元分析（NMA）在系统评价和健康技术评估中越来越受欢迎。但是，关于估计方法的属性以及评估一致性假设的方法仍然存在歧义。方法我们对多达5种干预措施的网络进行了模拟研究。我们研究了不同方法的特性，并为实际应用提供了建议。我们评估了复杂网络的3种不同模型的性能以及相应的全局方法，以评估一致性假设。这些模型是常客图论方法netmeta，贝叶斯混合处理比较（MTC）一致性模型，和MTC一致性模型，逐步删除导致杠杆图中确定的不一致的研究。结果我们发现，在高度不一致的情况下，没有一个评估的效果估计器产生可靠的结果，而在中等程度或没有不一致的情况下，MTC一致性模型和netmeta估计器的估计值显示出可接受的属性。我们还看到了对异质性数量的依赖。关于评估一致性假设的评估方法，没有一种适合。结论基于我们的结果，我们推荐一种实用的方法在NMA中进行实际应用。应该优先使用netmeta方法的估计器或贝叶斯MTC一致性模型的估计器。