Clinical trials have different designs: In late stage drug development, the parallel trial design is the most frequent one; however, the crossover design is not rare; different techniques are used to analyse their results. Although both designs measure the same treatment effect, combining parallel and crossover trials in a meta‐analysis is not straightforward. We present here a meta‐analysis method based on generalised estimating equation (GEE) regression to combine aggregated results of crossover and parallel trials using a marginal estimation approach. This method is based on the fixed effects meta‐analytic model; it allows combining average outcomes belonging to the exponential distributions obtained from trials of different designs and in particular from crossover trials with more than 2 periods and 2 treatments. By extending the methods proposed so far to combine the 2 trial designs, the GEE regression allows for adjusting for bias, such as a carry‐over effect typical in crossover trials. In this paper, the GEE meta‐analysis method is compared to the classical weighted average method with examples of published and simulated meta‐analyses. Although the GEE can account for crossover specificities, it is limited by the availability of detailed trial information often encountered with reports of these trials.

中文翻译：

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荟萃分析使用广义估计方程法结合了平行试验和交叉试验。

临床试验具有不同的设计：在药物开发的后期阶段，并行试验设计是最常见的设计；而并行试验设计是最常见的设计。但是，交叉设计并不罕见。使用不同的技术来分析其结果。尽管两种设计均能测量出相同的治疗效果，但在荟萃分析中将平行试验和交叉试验结合起来并非易事。我们在此提出一种基于广义估计方程（GEE）回归的荟萃分析方法，以使用边际估计方法将交叉试验和平行试验的汇总结果结合起来。该方法基于固定效应的荟萃分析模型；它允许将属于不同设计试验的指数分布的平均结局相结合，特别是从超过2个周期和2种治疗的交叉试验中得出的结果。通过扩展到目前为止提出的方法以结合这两种试验设计，GEE回归可以调整偏差，例如交叉试验中典型的残留效应。本文将GEE荟萃分析方法与经典加权平均方法进行比较，并结合已发表和模拟的荟萃分析实例。尽管GEE可以说明交叉的特异性，但受限于这些试验报告中经常遇到的详细试验信息的可用性。