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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从实时系统评价到元分析研究领域

由于许多领域的随机对照试验 (RCT) 和荟萃分析的数量迅速增加，因此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允许更高级别的 RCT 结果汇总，但不能充分涵盖整个领域的证据。“元分析研究领域”(MARD) 可能是一种聚合整个领域 RCT 数据的新方法。MARD 是对一个 PICO 无法涵盖的研究领域的实时系统评价。例如，抑郁症心理治疗的 MARD 涵盖了所有随机对照试验，比较所有类型的心理治疗对控制条件的影响，相互比较，药物治疗和联合治疗。它还涵盖了所有比较治疗形式的随机对照试验，对不同目标群体、抑郁症亚型和次要结果的影响。尽管构建 MARD 所需的时间和资源相当可观，但它们具有许多优势，包括对研究领域的全面和一致的概述以及传统方法无法进行的重要元分析研究。MARD 是一种很有前途的方法，可以将 RCT 的聚合提升到一个新的水平，并且以更详细的方式制定这种方法的方法非常相关。