School of Medicine, University of Wollongong, Australia; Illawarra Health and Medical Research Institute, Australia.
School of Medicine, University of Wollongong, Australia.
Contemp Clin Trials. 2021 Apr;103:106290. doi: 10.1016/j.cct.2021.106290. Epub 2021 Jan 24.
The Good Clinical Practice guideline identifies that data monitoring is an essential research activity. However, limited evidence exists on how to perform monitoring including the amount or frequency that is needed to ensure data quality. This study aims to explore the monitoring procedures that are implemented to ensure data quality in Australian clinical research studies.
Clinical studies listed on the Australian and New Zealand Clinical Trials Registry were invited to participate in a national cross-sectional, mixed-mode, multi-contact (postal letter and e-mail) web-based survey. Information was gathered about the types of data quality monitoring procedures being implemented.
Of the 3689 clinical studies contacted, 589 (16.0%) responded, of which 441 (77.4%) completed the survey. Over half (55%) of the studies applied source data verification (SDV) compared to risk-based targeted and triggered monitoring (10-11%). Conducting 100% on-site monitoring was most common for those who implemented the traditional approach. Respondents who did not conduct 100% monitoring, included 1-25% of data points for SDV, centralized or on-site monitoring. The incidence of adverse events and protocol deviations were the most likely factors to trigger a site visit for risk-based triggered (63% and 44%) and centralized monitoring (48% and 44%), respectively.
Instead of using more optimal risk-based approaches, small single-site clinical studies are conducting traditional monitoring procedures which are time consuming and expensive. Formal guidelines need to be improved and provided to all researchers for 'new' risk-based monitoring approaches.
《良好临床实践指南》指出，数据监测是一项重要的研究活动。然而，关于如何进行监测，包括需要多少或多频繁的数据监测来确保数据质量，目前证据有限。本研究旨在探讨澳大利亚临床研究中实施的监测程序，以确保数据质量。
邀请澳大利亚和新西兰临床试验注册中心列出的临床研究参与全国性的横断面、混合模式、多接触（邮寄信和电子邮件）的基于网络的调查。收集了正在实施的数据质量监测程序的类型信息。
在联系的 3689 项临床研究中，有 589 项（16.0%）做出回应，其中 441 项（77.4%）完成了调查。超过一半（55%）的研究应用了源数据验证（SDV），而基于风险的靶向和触发监测（10-11%）。对于采用传统方法的研究，进行 100%现场监测最为常见。对于那些不进行 100%监测的研究，包括对 SDV 进行 1-25%的数据点监测，以及集中式或现场监测。对于基于风险的触发监测（63%和 44%）和集中式监测（48%和 44%），不良事件和方案偏差的发生率最有可能触发现场访问。
小型单站点临床研究没有采用更优的基于风险的方法，而是采用传统的监测程序，这些程序既耗时又昂贵。需要改进和向所有研究人员提供正式的指南，以采用“新”的基于风险的监测方法。
