Sanofi Research and Development, Chilly-Mazarin, France.
Ividata Group, Levallois-Perret, France.
Stat Med. 2021 Feb 10;40(3):566-577. doi: 10.1002/sim.8789. Epub 2020 Oct 27.
The Matching-Adjusted Indirect Comparison method (MAIC) is a recent methodology that allows to perform indirect comparisons between two drugs assessed in two different studies, where individual patients data are available in only one of the two studies, the data of the other one being available in an aggregate format only. In this work, we have assessed the properties of the MAIC method and compared, through simulations, several ways of practical implementation of the method. We conclude that it is more efficient to match the treatment arms separately (match the two drugs to compare on one hand, and the control arms on the other hand) and use the Lasso technique to select the covariates for the matching step is better than matching a maximal set of covariates.
匹配调整间接比较法（MAIC）是一种最近的方法，可以在两个单独的研究中对两种药物进行间接比较，其中个体患者的数据仅在其中一个研究中可用，而另一个研究的数据仅以汇总格式可用。在这项工作中，我们评估了 MAIC 方法的性质，并通过模拟比较了该方法的几种实际实现方式。我们得出的结论是，分别匹配治疗组（一方面比较两种药物，另一方面比较对照臂）更有效，并且使用套索技术选择匹配步骤的协变量比匹配最大协变量集更好。
