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Vignette-Based Estimation of Utilities in Patients With Metastatic Triple-Negative Breast Cancer in Japan
Mao Yamaguchi1, Kensuke Moriwaki1, Tsuguo Iwatani2
1Division of Health Policy and Management, Department of Biomedical Science, College of Life Sciences, Ritsumeikan University, Kusatsu, Shiga, Japan; Comprehensive Unit for Health Economic Evidence Review and Decision Support (CHEERS), Research Organization of Science and Technology, Ritsumeikan University, Simogyo-ku, Kyoto, Japan.
Objectives:
To estimate utility values for patients with metastatic triple-negative breast cancer (mTNBC) and disutility due to treatment-related adverse events (AEs) using vignettes with the Japanese general population.
Methods:
Health states were developed to characterize the impact of mTNBC symptoms and AEs on health-related quality of life (HRQL), based on a literature review and interviews with clinical experts. Preferences for 10 different health states were assessed, including a progression-free (PF) for patients with TNBC, 6 health states with AEs during treatment with PF, and progression of disease. Utility values were estimated using the lead-time trade-off (LT-TTO) method and analyzed with a generalized estimating equation model. A total of 320 Japanese individuals from the general population participated, with 160 each from Tokyo and Osaka.
Results:
The mean utilities for the PF and progression of disease states were 0.702 (95% CI: 0.675-0.730) and 0.583 (95% CI: 0.547-0.618), respectively. Among AEs, nausea/vomiting had the greatest negative impact on HRQL (disutility = -0.936), while neutropenia had the least (disutility = -0.037).
Conclusions:
This study quantified utility weights and clarified the magnitude of the impact of AEs in Japanese patients with mTNBC. These findings highlight the importance of considering HRQL decline when evaluating the cost-effectiveness of mTNBC treatments. These data can inform future cost-effectiveness analyses for various mTNBC drugs while considering the preferences of the Japanese population. They can also be used to propose the optimal treatment for mTNBC.
