Department of Statistics, Iowa State University, Ames, USA.
Department of Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, USA.
BMC Med Res Methodol. 2023 Apr 3;23(1):79. doi: 10.1186/s12874-023-01896-7.
In network meta-analysis, estimation of a comparative effect can be performed for treatments that are connected either directly or indirectly. However, disconnected trial networks may arise, which poses a challenge to comparing all available treatments of interest. Several modeling approaches attempt to compare treatments from disconnected networks but not without strong assumptions and limitations. Conducting a new trial to connect a disconnected network can enable calculation of all treatment comparisons and help researchers maximize the value of the existing networks. Here, we develop an approach to finding the best connecting trial given a specific comparison of interest.
We present formulas to quantify the variation in the estimation of a particular comparative effect of interest for any possible connecting two-arm trial. We propose a procedure to identify the optimal connecting trial that minimizes this variation in effect estimation.
We show that connecting two treatments indirectly might be preferred to direct connection through a new trial, by leveraging information from the existing disconnected networks. Using a real network of studies on the use of vaccines in the treatment of bovine respiratory disease (BRD), we illustrate a procedure to identify the best connecting trial and confirm our findings via simulation.
Researchers wishing to conduct a connecting two-arm study can use the procedure provided here to identify the best connecting trial. The choice of trial that minimizes the variance of a comparison of interest is network dependent and it is possible that connecting treatments indirectly may be preferred to direct connection.
在网状荟萃分析中，可以对直接或间接关联的治疗方法进行比较效果估计。然而，可能会出现不连通的试验网络，这对比较所有感兴趣的现有治疗方法构成了挑战。有几种建模方法试图比较不连通网络中的治疗方法，但这些方法都存在假设和局限性。开展新的试验以连接不连通的网络，可以计算所有治疗方法的比较，并帮助研究人员最大限度地发挥现有网络的价值。在这里，我们提出了一种方法，以便在特定的比较研究中找到最佳的连接试验。
我们提出了一些公式，可以量化任何可能的两臂连接试验对特定比较效果估计的变异。我们提出了一种程序，以确定最小化该效果估计变异的最佳连接试验。
我们表明，通过利用现有不连通网络中的信息，间接连接两种治疗方法可能比通过新试验进行直接连接更优。我们使用关于疫苗在治疗牛呼吸道疾病（BRD）中的应用的研究网络，说明了一种确定最佳连接试验的程序，并通过模拟验证了我们的发现。
希望开展连接两臂试验的研究人员可以使用此处提供的程序来确定最佳的连接试验。选择最小化感兴趣比较的方差的试验取决于网络，并且间接连接治疗方法可能比直接连接更优。
