Drug Evaluation Committee Is the Population Adjustment Method Useful in Indirect Comparisons? Matching-Adjusted Indirect Comparison and Simulated Treatment Comparison
January 2022
The UK’s NICE (National Institute for Health and Care Excellence), which has been implementing cost-effectiveness evaluations since early on, has published 21 Technical Support Documents (TSDs) to date regarding statistical methods and other aspects of health economic evaluation.These documents serve as valuable references for Japan, which officially adopted cost-effectiveness analysis in 2019. The Data Science Subcommittee’s FY2021 Continuing Task Force 3 is organizing the topics covered in NICE’s TSDs and providing information deemed useful for conducting cost-effectiveness analyses in Japan.This report focuses on TSD 18, “Methods for population-adjusted indirect comparisons in submissions to NICE,” and addresses a situation commonly faced by companies(where a company’s own trials involve individual patient data, while trials by other companies are based only on population- or cohort-level data) for the Explanation of how to conduct indirect comparisons by adjusting for differences in the distribution of effect modifiers between trials—specifically, the methods known as Matching-Adjusted Indirect Comparison (MAIC) and Simulated Treatment Comparison (STC).In addition to providing an explanation of the content and theoretical background of these methods, this report presents performance evaluations based on simulation studies, introduces recent application examples, and provides implementation examples using R. While the number of application cases for these methods has been increasing in recent years—and examples have been observed even after their full-scale introduction in Japan—caution is required when applying them, as they rely on very strong assumptions.Therefore, we hope that referring to this report when conducting indirect comparisons will assist you in selecting the appropriate method and performing your analyses.
Japan Pharmaceutical Manufacturers Association (JPMA) Drug Evaluation Committee
Data Science Subcommittee FY2021 Continuing Task Force 3