Fneish Firas, Schaarschmidt Frank, Fortwengel Gerhard
Institute of Cell Biology and Biophysics, Department of Biostatistics, Leibniz University Hannover, 30419 Hannover, Germany.
Faculty III Media Information and Design, Hochschule Hannover, 30539 Hannover, Germany.
Curr Ther Res Clin Exp. 2021 Aug 28;95:100643. doi: 10.1016/j.curtheres.2021.100643. eCollection 2021.
Regulatory authorities have encouraged the usage of a monitoring (RBM) system in clinical trials before trial initiation for detection of potential risks and inclusion of a mitigation plan in the monitoring strategy. Several RBM tools were developed after the International Council for Harmonization gave sponsors the flexibility to initiate an approach to enhance quality management in a clinical trial. However, various studies have demonstrated the need for improvement of the available RBM tools as each does not provide a comprehensive overview of the characteristics, focus, and application. This research lays out a rationale for a risk methodology assessment (RMA) within the RBM system. The core purpose of RMA is to deliver a scientifically based evaluation and decision of any potential risk in a clinical trial. Thereby, a monitoring plan can be developed to elude prior identified risk outcome. To demonstrate RMA's theoretical approach in practice, a Shiny web application (R Foundation for Statistical Computing) was designed to describe the assessment process of risk analysis and visualization tools that eventually aid in focusing monitoring activities. RMA focuses on the identification of an individual risk and visualizes its weight on the trial. The scoring algorithm of the presented approach computes the assessment of the individual risk in a radar plot and computes the overall score of the trial. Moreover, RMA's novelty lies in its ability to decrease biased decision making during risk assessment by categorizing risk influence and detectability; a characteristic pivotal to serve RBM in assessing risks, and in contributing to a better understanding in the monitoring technique necessary for developing a functional monitoring plan. Future research should focus on validating the power of RMAs to demonstrate its efficiency. This would facilitate the process of characterizing the strengths and weaknesses of RMA in practice.
监管机构鼓励在临床试验启动前使用监测（基于风险的监测，RBM）系统，以检测潜在风险，并在监测策略中纳入缓解计划。在国际协调理事会给予申办者在临床试验中采用增强质量管理方法的灵活性之后，开发了几种RBM工具。然而，各种研究表明，现有的RBM工具需要改进，因为每种工具都没有全面概述其特征、重点和应用。本研究阐述了RBM系统内风险方法评估（RMA）的基本原理。RMA的核心目的是对临床试验中的任何潜在风险进行科学评估并做出决策。因此，可以制定监测计划以避免先前确定的风险结果。为了在实践中展示RMA的理论方法，设计了一个Shiny网络应用程序（R统计计算基金会）来描述风险分析和可视化工具的评估过程，最终有助于集中监测活动。RMA专注于识别个体风险，并直观显示其在试验中的权重。所提出方法的评分算法在雷达图中计算个体风险的评估，并计算试验的总体得分。此外，RMA的新颖之处在于它能够通过对风险影响和可检测性进行分类来减少风险评估期间的偏差决策；这一特征对于RBM评估风险以及有助于更好地理解制定有效监测计划所需的监测技术至关重要。未来的研究应专注于验证RMA的功效以证明其效率。这将有助于在实践中描述RMA的优缺点。
