Extending methods for investigating the relationship between treatment effect and baseline risk from pairwise meta-analysis to network meta-analysis
Extending methods for investigating the relationship between treatment effect and baseline risk from pairwise meta-analysis to network meta-analysis
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DOI：
10.1002/sim.5539
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发表时间：
2013-02-28
影响因子：
2
通讯作者：
Sutton, Alex J.
中科院分区：
文献类型：
--
作者：
Achana, Felix A.;Cooper, Nicola J.;Sutton, Alex J.
基线风险是未测量但重要的患者水平特征的代表，这些特征可能是治疗效果的修饰符，并且是荟萃分析中异质性的潜在来源。使用安慰剂组中观察到的事件发生率并考虑协变量中的测量误差，为成对荟萃分析开发了基线风险调整模型，以确保获得无偏倚的关系估计值。我们的目标是将这些方法扩展到网络荟萃分析中，其中调整非干预组事件率的基线不平衡以减少异质性和可能的不一致性是有意义的。这一目标是复杂的网络荟萃分析的协变量有时会丢失，因为事实上，不是所有的研究在一个网络可能有一个非积极的干预arm.A随机效应荟萃回归模型，允许纳入多臂试验和试验没有非干预的手臂开发。使用WinBUGS软件在贝叶斯框架内进行分析。使用两个例子说明了该方法：（一）干预措施，以促进功能烟雾报警器的所有权由有孩子的家庭和（二）镇痛剂，以减少术后吗啡消费后的大手术。结果表明，在烟雾报警器的例子中没有基线效应的证据，但止痛剂的例子表明，调整可以大大减少异质性，提高整体模型拟合。版权所有（c）2012约翰威利父子有限公司
Baseline risk is a proxy for unmeasured but important patient-level characteristics, which may be modifiers of treatment effect, and is a potential source of heterogeneity in meta-analysis. Models adjusting for baseline risk have been developed for pairwise meta-analysis using the observed event rate in the placebo arm and taking into account the measurement error in the covariate to ensure that an unbiased estimate of the relationship is obtained. Our objective is to extend these methods to network meta-analysis where it is of interest to adjust for baseline imbalances in the non-intervention group event rate to reduce both heterogeneity and possibly inconsistency. This objective is complicated in network meta-analysis by this covariate being sometimes missing, because of the fact that not all studies in a network may have a non-active intervention arm. A random-effects meta-regression model allowing for inclusion of multi-arm trials and trials without a non-intervention' arm is developed. Analyses are conducted within a Bayesian framework using the WinBUGS software. The method is illustrated using two examples: (i) interventions to promote functional smoke alarm ownership by households with children and (ii) analgesics to reduce post-operative morphine consumption following a major surgery. The results showed no evidence of baseline effect in the smoke alarm example, but the analgesics example shows that the adjustment can greatly reduce heterogeneity and improve overall model fit. Copyright (c) 2012 John Wiley & Sons, Ltd.