YCU Center for Novel and Exploratory Clinical Trials, Yokohama City University Hospital, 1-1- 1 Fukuura, Yokohama, Kanagawa, Japan.
Department of Health Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, Japan.
Ther Innov Regul Sci. 2024 Nov;58(6):1006-1013. doi: 10.1007/s43441-024-00695-6. Epub 2024 Sep 3.
The results of observational studies using real-world data, known as real-world evidence, have gradually started to be used in drug development and decision-making by policymakers. A good quality management system-a comprehensive system of process, data, and documentation to ensure quality-is important in obtaining real-world evidence. A risk-based approach is a common quality management system used in interventional studies. We used a quality management system and risk-based approach in an observational study on a designated intractable disease. Our multidisciplinary team assessed the risks of the real-world data study comprehensively and systematically. When using real-world data and evidence to support regulatory decisions, both the quality of the database and the validity of the outcome are important. We followed the seven steps of the risk-based approach for both database selection and research planning. We scored the risk of two candidate databases and chose the Japanese National Database of designated intractable diseases for this study. We also conducted a quantitative assessment of risks associated with research planning. After prioritizing the risks, we revised the research plan and outcomes to reflect the risk-based approach. We concluded that implementing a risk-based approach is feasible for an observational study using real-world data. Evaluating both database selection and research planning is important. A risk-based approach can be essential to obtain robust real-world evidence.
真实世界数据（real-world data，RWD）观察性研究的结果，也被称为真实世界证据，已逐渐开始被药物开发者和决策者用于药物研发和决策。良好的质量管理体系（一种确保质量的全面流程、数据和文件管理系统）对于获取真实世界证据至关重要。基于风险的方法是一种常用于干预性研究的常见质量管理系统。我们在一项指定的难治性疾病的观察性研究中使用了质量管理系统和基于风险的方法。我们的多学科团队全面系统地评估了真实世界数据研究的风险。当使用真实世界数据和证据来支持监管决策时，数据库的质量和结果的有效性都很重要。我们遵循基于风险的方法的七个步骤，分别用于数据库选择和研究规划。我们对两个候选数据库的风险进行了评分，并选择日本指定的难治性疾病国家数据库用于这项研究。我们还对研究规划相关风险进行了定量评估。在对风险进行优先级排序后，我们修订了研究计划和结果，以反映基于风险的方法。我们得出结论，对于使用真实世界数据的观察性研究，实施基于风险的方法是可行的。评估数据库选择和研究规划都很重要。基于风险的方法对于获得稳健的真实世界证据至关重要。
