Dose-response meta-analysis of differences in means.
Dose-response meta-analysis of differences in means.
复制标题
DOI：
10.1186/s12874-016-0189-0
复制
发表时间：
2016-08-02
影响因子：
4
通讯作者：
Orsini N
中科院分区：
文献类型：
--
作者：
Crippa A;Orsini N
荟萃分析方法经常被用来结合以相对风险表示的剂量反应结果。然而，当根据量化结果的不同来总结结果时，还没有建立起方法论。我们提出了一个分两个阶段的方法。在每项研究(第一阶段)中，考虑数据点的协方差(均值差异、标准化均值差异)，估计灵活的剂量-反应模型。然后使用多变量随机效应模型(第二阶段)组合描述特定研究曲线的参数，以解决研究之间的异质性。该方法具有较强的通用性，可适用于多种参数函数。与传统的非线性模型(如Emax、Logistic模型)相比，Spline模型不假定任何预先指定的剂量-反应曲线。Spline模型允许包含少量剂量水平的研究，而且几乎任何形状，甚至非单调形状，都可以仅使用两个参数进行估计。我们使用抗精神病药物阿立哌唑的五项临床试验的剂量反应数据说明了该方法，并对精神分裂症患者的症状改善进行了说明。使用阳性和阴性症状量表(PANSS)，合并结果表明，对于19.32 mg/天的阿立哌唑，平均PANSS评分的最大变化等于10.40(95%可信区间7.48，13.30)，呈非线性关系。在PANSS评分中没有观察到高于这个值的实质性变化。每天10.43毫克的估计剂量被发现产生了最大预测反应的80%。应采用所描述的方法，将多项研究的量化结果的相关差异结合起来。敏感性分析是评估总体剂量-反应曲线对不同建模策略的稳健性的有用工具。开发了一个用户友好的R包，以方便从业人员的应用。
Meta-analytical methods are frequently used to combine dose-response findings expressed in terms of relative risks. However, no methodology has been established when results are summarized in terms of differences in means of quantitative outcomes. We proposed a two-stage approach. A flexible dose-response model is estimated within each study (first stage) taking into account the covariance of the data points (mean differences, standardized mean differences). Parameters describing the study-specific curves are then combined using a multivariate random-effects model (second stage) to address heterogeneity across studies. The method is fairly general and can accommodate a variety of parametric functions. Compared to traditional non-linear models (e.g. Emax, logistic), spline models do not assume any pre-specified dose-response curve. Spline models allow inclusion of studies with a small number of dose levels, and almost any shape, even non monotonic ones, can be estimated using only two parameters. We illustrated the method using dose-response data arising from five clinical trials on an antipsychotic drug, aripiprazole, and improvement in symptoms in shizoaffective patients. Using the Positive and Negative Syndrome Scale (PANSS), pooled results indicated a non-linear association with the maximum change in mean PANSS score equal to 10.40 (95 % confidence interval 7.48, 13.30) observed for 19.32 mg/day of aripiprazole. No substantial change in PANSS score was observed above this value. An estimated dose of 10.43 mg/day was found to produce 80 % of the maximum predicted response. The described approach should be adopted to combine correlated differences in means of quantitative outcomes arising from multiple studies. Sensitivity analysis can be a useful tool to assess the robustness of the overall dose-response curve to different modelling strategies. A user-friendly R package has been developed to facilitate applications by practitioners.