审查对外部数据的使用情况和对顺序多重分配随机试验报告标准的更新
Isaac J Egesa1, Laura Bonnett1, Richard Emsley2
1Health Data Science, Institute of Population Health, University of Liverpool, Liverpool, UK.
Clinical trials (London, England)
|November 5, 2025
概括
顺序多重分配随机试验 (SMART) 是复杂的. 这次审查发现80个SMART研究中的报告不一致,限制了透明度和可重复性. 为了更好地开发适应性干预,需要改进指导和外部数据的使用.
科学领域:
- 临床试验方法论 临床试验方法论
- 适应性干预措施 适应性干预
- 医疗保健服务研究 医疗服务研究
背景情况:
- 顺序多重分配随机试验 (SMART) 是适应性干预的黄金标准,但复杂且昂贵.
- 对SMART日益增长的兴趣需要改进实施指导和最佳实践.
- 整合外部数据可以提高SMART设计,实施和分析的效率.
研究的目的:
- 识别所有已发表的SMART试验.
- 总结他们的设计,行为和报告实践.
- 评估在 SMART 实施中外部数据的使用情况.
主要方法:
- 搜索了主要数据库 (PubMed,Medline,PsycINFO,Scopus,Web of Science) 的SMART试验,截至2024年6月30日.
- 定义的外部数据是非模拟的个人患者数据,收集在主要的SMART之外.
- 在审查中包括了80个SMART试验.
主要成果:
- 35个 (44%) 的SMART试验已经完成,45个 (56%) 的试验正在进行中.
- 大多数试验 (93%) 使用了两个随机化阶段,第一阶段专注于主要干预效应 (81%).
- 报告对于样本大小,统计软件和数据缺失等关键方面是不充分的. 其中有17个 (21%) 提及使用外部数据 (电子健康记录,注册表) 的试验.
结论:
- 智能设计越来越多地使用,但报告不一致,阻碍了透明度,可复制性和转化为常规护理.
- 在SMART试验中对外部数据的有限使用归因于方法和基础设施方面的挑战以及缺乏报告标准.
- 需要扩展CONSORT和SPIRIT指南,包括对外部数据的报告标准,以提高SMART的效率和通用性.
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