Because of the rapidly increasing number of randomised controlled trials (RCTs) and meta-analyses in many fields, there is an urgent need to step up from meta-analyses to higher levels of aggregation of outcomes of RCTs. Network meta-analyses and umbrella reviews allow higher levels of aggregation of RCT outcomes, but cannot adequately cover the evidence for a whole field. The ‘Meta-Analytic Research Domain’ (MARD) may be a new methodology to aggregate RCT data of a whole field. A MARD is a living systematic review of a research domain that cannot be covered by one PICO. For example, a MARD of psychotherapy for depression covers all RCTs comparing the effects of all types of psychotherapy to control conditions, to each other, to pharmacotherapy and combined treatment. It also covers all RCTs comparing treatment formats, the effects in different target groups, subtypes of depression and secondary outcomes. Although the time and resources needed to build a MARD are considerable, they offer many advantages, including a comprehensive and consistent overview of a research field and important meta-analytic studies that cannot be conducted with conventional methods. MARDs are a promising method to step up the aggregation of RCTs to a next level and it is highly relevant to work out the methods of this approach in a more detailed way.

中文翻译：

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从实时系统评价到荟萃分析研究领域


由于许多领域的随机对照试验（RCT）和荟萃分析数量迅速增加，迫切需要从荟萃分析升级到更高水平的随机对照试验结果汇总。网络荟萃分析和伞式审查可以对随机对照试验结果进行更高水平的汇总，但无法充分覆盖整个领域的证据。 “元分析研究领域”（MARD）可能是一种聚合整个领域的 RCT 数据的新方法。 MARD 是对单个 PICO 无法涵盖的研究领域进行的实时系统回顾。例如，抑郁症心理治疗的 MARD 涵盖了所有随机对照试验，比较了控制病情的所有类型的心理治疗相互之间、药物治疗和联合治疗的效果。它还涵盖了比较治疗形式、不同目标群体的效果、抑郁症亚型和次要结果的所有随机对照试验。尽管建立 MARD 所需的时间和资源相当多，但它们提供了许多优势，包括对研究领域的全面一致的概述以及使用传统方法无法进行的重要荟萃分析研究。 MARD 是一种很有前途的方法，可将 RCT 的汇总提升到一个新的水平，并且以更详细的方式制定该方法具有高度相关性。