Improving the Transferability of Global RCT Data to Inform Cost-Effectiveness Models in Japan: A Structured Framework for C2H Submissions

Author(s)

Alex Turner, PhD1, Yoshie Onishi, DrPH, RPh2, Mariko Nomoto, MBA2, Claire Leboucher, MSc3, Clement Francois, MSc, PhD4.
1Putnam, London, United Kingdom, 2Putnam, Tokyo, Japan, 3Putnam, Lyon, France, 4Putnam, Paris, France.
OBJECTIVES: To develop a structured methodological framework that supports the evaluation and improvement of the transferability of global randomized controlled trial (RCT) data for cost-effectiveness (CE) modelling in Japan, in line with the requirements of CORE 2 Health (C2H) guidance.
METHODS: The framework was developed through a multi-step process:
  1. Targeted Literature Review: Identification and synthesis of best practice recommendations from international health technology assessment (HTA) bodies and academic literature related to the transferability of clinical evidence.
  2. Comparative Analysis: Mapping key differences between Japanese and non-Japanese healthcare contexts, including clinical practice patterns, patient characteristics, and treatment pathways.
  3. Integration of Real-World Evidence (RWE): Consideration of practical approaches for integrating local RWE to support assessment of representativeness and effect modification.

RESULTS: The resulting framework consists of a two-step process:
Step 1 - Assessment of Treatment Effect Heterogeneity
  • Conduct subgroup and interaction analyses within the global RCT to assess potential heterogeneity in treatment effect between Japanese and non-Japanese populations.
  • If no significant heterogeneity is observed, global estimates may be considered applicable. If heterogeneity is present, Japanese-specific estimates are preferred.
Step 2 - Evaluation of Population Representativeness
  • Identify key clinical and demographic effect modifiers through expert input and literature.
  • Compare the distribution of these modifiers in the relevant RCT subgroup to Japanese real-world data (RWD). If existing datasets are insufficient, consider de novo analyses or expert elicitation.
  • Where mismatch exists, apply statistical adjustment methods (e.g., reweighting) to align RCT data with the Japanese target population, enhancing transferability.

CONCLUSIONS: This structured framework offers a practical approach to formally assess and improve the relevance of global RCT data for CE modelling in Japan. By incorporating both methodological rigor and local clinical context, it enables more robust, locally aligned submissions to C2H. Early integration of RWD and expert insight is critical to support successful application of this framework.

Conference/Value in Health Info

2025-11, ISPOR Europe 2025, Glasgow, Scotland

Value in Health, Volume 28, Issue S2

Code

EE547

Topic

Economic Evaluation, Health Technology Assessment

Topic Subcategory

Trial-Based Economic Evaluation

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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