MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, 90 High Holborn 2nd Floor, London, WC1V 6LJ, UK.
Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK.
Trials. 2019 Apr 17;20(1):227. doi: 10.1186/s13063-019-3301-z.
Triggered monitoring in clinical trials is a risk-based monitoring approach where triggers (centrally monitored, predefined key risk and performance indicators) drive the extent, timing, and frequency of monitoring visits. The TEMPER study used a prospective, matched-pair design to evaluate the use of a triggered monitoring strategy, comparing findings from triggered monitoring visits with those from matched control sites. To facilitate this study, we developed a bespoke risk-based monitoring system: the TEMPER Management System.
The TEMPER Management System comprises a web application (the front end), an SQL server database (the back end) to store the data generated for TEMPER, and a reporting function to aid users in study processes such as the selection of triggered sites. Triggers based on current practice were specified for three clinical trials and were implemented in the system. Trigger data were generated in the system using data extracted from the trial databases to inform the selection of triggered sites to visit. Matching of the chosen triggered sites with untriggered control sites was also performed in the system, while data entry screens facilitated the collection and management of the data from findings gathered at monitoring visits.
There were 38 triggers specified for the participating trials. Using these, 42 triggered sites were chosen and matched with control sites. Monitoring visits were carried out to all sites, and visit findings were entered into the TEMPER Management System. Finally, data extracted from the system were used for analysis.
The TEMPER Management System made possible the completion of the TEMPER study. It implemented an approach of standardising the automation of current-practice triggers, and the generation of trigger data to inform the selection of triggered sites to visit. It also implemented a matching algorithm informing the selection of matched control sites. We hope that by publishing this paper it encourages other trialists to share their approaches to, and experiences of, triggered monitoring and other risk-based monitoring systems.
临床试验中的触发式监测是一种基于风险的监测方法，其中触发因素（集中监测、预先设定的关键风险和绩效指标）驱动监测访问的范围、时间和频率。TEMPER 研究采用前瞻性配对设计来评估触发式监测策略的使用，比较触发式监测访问的结果与配对对照点的结果。为了便于这项研究，我们开发了一个定制的基于风险的监测系统：TEMPER 管理系统。
TEMPER 管理系统包括一个网络应用程序（前端）、一个 SQL 服务器数据库（后端），用于存储为 TEMPER 生成的数据，以及一个报告功能，以帮助用户完成研究过程，如触发点的选择。为三个临床试验指定了基于当前实践的触发因素，并在系统中实现了这些触发因素。使用从试验数据库中提取的数据在系统中生成触发数据，以便为要访问的触发点选择提供信息。系统还对选定的触发点与未触发的对照点进行匹配，而数据输入屏幕则方便了从监测访问中收集的数据的收集和管理。
为参与的试验指定了 38 个触发因素。使用这些触发因素，选择了 42 个触发点并与对照点匹配。对所有站点进行了监测访问，并将访问结果输入到 TEMPER 管理系统中。最后，从系统中提取数据进行分析。
TEMPER 管理系统使 TEMPER 研究得以完成。它实现了一种标准化当前实践触发的自动化方法，并生成触发数据，以便为要访问的触发点选择提供信息。它还实现了一个匹配算法，为选择配对的对照点提供信息。我们希望通过发表这篇论文，鼓励其他试验人员分享他们在触发式监测和其他基于风险的监测系统方面的方法和经验。
