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External Control Arms in Japan: A Systematic Case Analysis of Documented Regulatory Implementation and Uncertainty
Suguru Okami1, Alexandros Sagkriotis2
1Integrated Evidence Generation, Bayer Yakuhin Ltd., Osaka, Japan.
Abstract:
External control arms (ECAs) have emerged as important tools to provide benchmark evidence on comparator effectiveness and thereby support regulatory decision making in situations where randomized controlled trials are difficult to conduct. However, how key methodological elements for ECAs are documented and implemented in practice and how residual uncertainty is managed at the time of approval remain unclear. Regulatory approvals of new medical products in Japan between 2019 and 2024 were systematically screened to identify cases employing ECAs. Among 674 eligible approvals screened from 835 approvals identified, 23 cases using ECAs were included and evaluated using a structured framework of 20 key attributes derived from regulatory guidance and methodological recommendations across planning, selection, design, analysis, and reporting domains. The post-marketing requirements associated with each approval were also analyzed to assess how residual uncertainty was addressed following approval. ECAs were predominantly used in settings characterized by rare diseases and small patient populations. Although attributes related to study planning and data-source selection were relatively well described in public documentation, there was substantial heterogeneity in the documentation of design and analysis elements. In particular, explicit specifications of estimands and approaches to handling intercurrent events and missing data were inconsistently described. Residual uncertainty was frequently addressed through post-marketing requirements, often involving studies of efficacy considerations and long-term surveillance, supporting a lifecycle-based approach to uncertainty management. These findings highlight opportunities to enhance transparency and consistency in the documentation of ECA-based evidence and to further develop structured approaches to uncertainty management in regulatory practice.
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