Strategies to Address Current Challenges in Real-World Evidence Generation in Japan.

IF 1.9 Q3 PHARMACOLOGY & PHARMACY
Thomas Laurent, Dimitra Lambrelli, Ryozo Wakabayashi, Takahiro Hirano, Ryohei Kuwatsuru
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引用次数: 1

Abstract

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.

应对日本现实世界证据生成中当前挑战的策略。
真实世界证据生成(RWE),即使用真实世界数据描述患者特征或治疗模式(RWD),作为决策工具在日本迅速流行起来。本综述的目的是总结日本与药物流行病学相关的RWE产生的挑战,并提出应对这些挑战的策略。我们首先关注与数据相关的问题,包括RWD来源缺乏透明度,不同护理环境之间的联系,临床结果的定义,以及用于研究目的时RWD的总体评估框架。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,因此研究设计的透明报告对利益相关者至关重要。在本综述中,我们考虑了不同的偏倚来源和时变混杂因素,以及潜在的研究设计和方法学解决方案。此外,考虑到RWD来源相关的限制,对定义不确定性、错误分类和未测量混杂因素实施强有力的评估将提高RWE的可信度,日本的工作组正在强烈考虑这一点。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生成过程中的不同偏差来源和稳健性,将提高利益相关者和当地决策者的可信度。
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来源期刊
Drugs - Real World Outcomes
Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-
CiteScore
3.60
自引率
5.00%
发文量
49
审稿时长
8 weeks
期刊介绍: Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.
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