临床研究中的源数据验证 (SDV) 质量:一个范围审查.
Muayad Hamidi1, Eric L Eisenstein2, Maryam Y Garza3
1University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Journal of clinical and translational science
|December 16, 2024
概括
在临床试验中评估源数据验证 (SDV) 质量对于基于风险的监测至关重要. 然而,目前的文献缺乏SDV的标准化方法和绝对准确度指标,这阻碍了设计实施的有效质量.
科学领域:
- 临床翻译科学 临床翻译科学
- 临床试验监测 临床试验监测
- 监管科学 监管科学
背景情况:
- 源数据验证 (SDV) 在临床翻译科学中经常被讨论.
- 发表的关于SDV质量的评估,特别是准确性的评估很少.
- 这种稀缺性阻碍了基于风险和减少监测策略的发展.
研究的目的:
- 进行关于SDV质量的文献范围审查.
- 具体确定评估SDV准确性的报告.
- 了解有关SDV质量指标的当前知识状态.
主要方法:
- 一个全面的范围审查SDV和临床试验监测文献.
- 系统选识别的物品.
- 基于研究设计,SDV背景和报告质量措施的文章总结.
主要成果:
- 在SDV方法,质量领域和结果措施中发现了显著的异质性.
- 研究间的差异性使得无法直接比较或汇集结果.
- 在经过审查的文献中,没有确定SDV准确性的绝对指标.
结论:
- 目前还无法对SDV过程精度进行明确的描述.
- 在不了解未检测到关键发现 (敏感性) 的风险的情况下降低SDV与良好的临床实践和设计质量相矛盾.
- 需要对SDV准确性的参考估计,以设计有效的基于风险的,减少SDV的流程.
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