Network meta-analysis including treatment by covariate interactions: Consistency can vary across covariate values.
Network meta-analysis including treatment by covariate interactions: Consistency can vary across covariate values.
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DOI：
10.1002/jrsm.1257
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发表时间：
2017-12
影响因子：
9.8
通讯作者：
Dias S
中科院分区：
文献类型：
--
作者：
Donegan S;Welton NJ;Tudur Smith C;D'Alessandro U;Dias S
许多评论旨在比较多种治疗方法并报告按亚组（例如，按疾病严重程度）分层的结果。在这种情况下，包括协变量相互作用治疗的网络荟萃分析模型可以估计所有治疗配对对每个患者亚组的相对效果。这些模型基于两个关键假设：治疗效果的一致性和相互作用回归系数的一致性。一致性可能会有所不同，具体取决于评估一致性的协变量值。为了进行有效的推理，我们需要对相关协变量值范围的一致性充满信心。在本文中，我们演示了如何根据各种协变量值的直接和间接证据评估治疗效果的一致性。使用目视检查、不一致性估计和概率来评估一致性。该方法应用于个体患者数据集，使用协变量年龄比较青蒿素联合疗法治疗儿童单纯性疟疾的情况。每次比较中，不一致的程度似乎随着年龄的增加而减小。对于一项比较，1 岁的直接和间接证据不同 (P = .05)，这使所有比较的 1 岁结果受到质疑。当拟合包括相互作用的模型时，必须在试验中包含的协变量范围内评估直接和间接证据的一致性。临床推论仅对结果一致的协变量值有效。
Many reviews aim to compare numerous treatments and report results stratified by subgroups (eg, by disease severity). In such cases, a network meta‐analysis model including treatment by covariate interactions can estimate the relative effects of all treatment pairings for each subgroup of patients. Two key assumptions underlie such models: consistency of treatment effects and consistency of the regression coefficients for the interactions. Consistency may differ depending on the covariate value at which consistency is assessed. For valid inference, we need to be confident of consistency for the relevant range of covariate values. In this paper, we demonstrate how to assess consistency of treatment effects from direct and indirect evidence at various covariate values. Consistency is assessed using visual inspection, inconsistency estimates, and probabilities. The method is applied to an individual patient dataset comparing artemisinin combination therapies for treating uncomplicated malaria in children using the covariate age. The magnitude of the inconsistency appears to be decreasing with increasing age for each comparison. For one comparison, direct and indirect evidence differ for age 1 (P = .05), and this brings results for age 1 for all comparisons into question. When fitting models including interactions, the consistency of direct and indirect evidence must be assessed across the range of covariates included in the trials. Clinical inferences are only valid for covariate values for which results are consistent.
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影响因子：
3.7
作者：
Donegan S;Williams L;Dias S;Tudur-Smith C;Welton N
通讯作者：
Welton N
影响因子：
9.8
作者：
Lu, Guobing;Welton, Nicky J.;Ades, A. E.
通讯作者：
Ades, A. E.
影响因子：
2
作者：
Cooper, Nicola J.;Sutton, Alex J.;Welton, Nicky J.
通讯作者：
Welton, Nicky J.
影响因子：
2
作者：
Riley, Richard D.;Lambert, Paul C.;Boutitie, Florent
通讯作者：
Boutitie, Florent
影响因子：
2
作者：
Donegan, Sarah;Williamson, Paula;Smith, Catrin Tudur
通讯作者：
Smith, Catrin Tudur