Department of Health Sciences, University of Leicester, Leicester LE1 7RH, U.K.
Stat Med. 2013 Feb 28;32(5):752-71. doi: 10.1002/sim.5539. Epub 2012 Aug 2.
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.
基线风险是未测量但重要的患者水平特征的替代指标，它可能是治疗效果的修饰因子，也是荟萃分析中异质性的潜在来源。已经为基于对比例的荟萃分析开发了调整基线风险的模型，使用安慰剂组中的观察到的事件率，并考虑协变量中的测量误差，以确保获得无偏估计值。我们的目标是将这些方法扩展到网络荟萃分析中，在网络荟萃分析中，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很有意义的。在网络荟萃分析中，由于并非网络中的所有研究都有非活性干预臂，因此这个协变量有时会缺失，这使得目标变得复杂。开发了一个允许包含多臂试验和没有“非干预”臂的试验的随机效应荟萃回归模型。使用 WinBUGS 软件在贝叶斯框架内进行分析。该方法通过两个示例进行说明：（i）通过有孩子的家庭促进功能性烟雾报警器拥有率的干预措施，以及（ii）减少大手术后吗啡消耗的镇痛药。结果表明，在烟雾报警器示例中没有基线效应的证据，但镇痛药示例表明，这种调整可以大大减少异质性并提高整体模型拟合度。
