1. QALY-type preference and willingness-to-pay among end-of-life patients with cancer treatments: a pilot study using discrete choice experiment.
- Author
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Yin, Yue, Peng, Qian, Ma, Longhao, Dong, Yi, Sun, Yinan, Xu, Silu, Ding, Nianyang, Liu, Xiaolin, Zhao, Mingye, Tang, Yaqian, Mei, Zhiqing, Shao, Hanqiao, Yan, Dan, and Tang, Wenxi
- Subjects
WILLINGNESS to pay ,HEALTH care rationing ,CANCER patients ,NON-small-cell lung carcinoma ,PILOT projects - Abstract
Purpose: Quality-adjusted life-year (QALY) is a dominant measurement of health gain in economic evaluations for pricing drugs. However, end-of-life (EoL) patients' preference for QALY gains in life expectancy (LE) and quality of life (QoL) during different disease stages remains unknown and is seldom involved in decision-making. This study aims to measure preferences and willingness-to-pay (WTP) towards different types of QALY gain among EoL cancer patients. Methods: We attributed QALY gain to four types, gain in LE and QoL, respectively, and during both progression-free survival (PFS) and post-progression survival (PPS). A discrete choice experiment including five attributes (the four QALY attributes and one cost attribute) with three levels each was developed and conducted with 85 Chinese advanced non-small cell lung cancer patients in 2022. All levels were set with QALY gain/cost synthesised from research on anti-lung cancer drugs recently listed by Chinese National Healthcare Security Administration. Each respondent answered six choice tasks in a face-to-face interview. The data were analysed using mixed logit models. Results: Patients valued LE-related QALY gain in PFS most, with a relative importance of 81.8% and a WTP of $43,160 [95% CI 26,751 ~ 59,569] per QALY gain. Respondents consistently preferred LE-related to QoL-related QALY gain regardless of disease stage. Patients with higher income or lower education levels tended to pay more for QoL-related QALY gain. Conclusion: Our findings suggest a prioritised resource allocation to EoL-prolonging health technologies. Given the small sample size and large individual heterogeneity, a full-scale study is needed to provide more robust results. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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