Laurent Thomas, Lambrelli Dimitra, Wakabayashi Ryozo, Hirano Takahiro, Kuwatsuru Ryohei
Real-World Evidence and Data Assessment (READS), Graduate School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo-ku, Tokyo, 113-8421, Japan.
Clinical Study Support Inc., 2F Daiei Bldg., 1-11-20 Nishiki Naka-ku, Nagoya, 460-0003, Japan.
Drugs Real World Outcomes. 2023 Jun;10(2):167-176. doi: 10.1007/s40801-023-00371-5. Epub 2023 May 13.
The generation of real-world evidence (RWE), which describes patient characteristics or treatment patterns using real-world data (RWD), is rapidly growing more popular as a tool for decision-making in Japan. The aim of this review was to summarize challenges to RWE generation in Japan related to pharmacoepidemiology, and to propose strategies to address some of these challenges. We first focused on data-related issues, including the lack of transparency of RWD sources, linkage across different care settings, definitions of clinical outcomes, and the overall assessment framework of RWD when used for research purposes. Next the study reviewed methodology-related challenges. As lack of design transparency impairs study reproducibility, transparent reporting of study design is critical for stakeholders. For this review, we considered different sources of biases and time-varying confounding, along with potential study design and methodological solutions. Additionally, the implementation of robust assessment of definition uncertainty, misclassification, and unmeasured confounders would enhance RWE credibility in light of RWD source-related limitations, and is being strongly considered by task forces in Japan. Overall, the development of guidance for best practices on data source selection, design transparency, and analytical methods to address different sources of biases and robustness in the process of RWE generation will enhance credibility for stakeholders and local decision-makers.
利用真实世界数据(RWD)描述患者特征或治疗模式的真实世界证据(RWE)的生成,作为一种决策工具在日本正迅速变得更受欢迎。本综述的目的是总结日本在RWE生成方面与药物流行病学相关的挑战,并提出应对其中一些挑战的策略。我们首先关注与数据相关的问题,包括RWD来源缺乏透明度、不同医疗环境之间的关联、临床结局的定义以及用于研究目的时RWD的整体评估框架。接下来,该研究回顾了与方法相关的挑战。由于缺乏设计透明度会损害研究的可重复性,研究设计的透明报告对利益相关者至关重要。对于本综述,我们考虑了不同来源的偏差和随时间变化的混杂因素,以及潜在的研究设计和方法学解决方案。此外,鉴于RWD来源相关的局限性,对定义不确定性、错误分类和未测量混杂因素进行稳健评估的实施将提高RWE的可信度,日本的特别工作组正在大力考虑这一点。总体而言,制定关于数据源选择、设计透明度和分析方法的最佳实践指南,以解决RWE生成过程中不同来源的偏差和稳健性问题,将提高利益相关者和地方决策者的可信度。