OBJECTIVES: Health gain, including gain in life expectancy (LE) and quality of life (QoL), is always measured by quality-adjusted life-year (QALY) and has been increasingly valued in health resource allocation. Studies show that preferences toward QALY gains in LE and QoL are usually independent and inconsistent before and after disease progression. Nevertheless, preferences of end-of-life (EoL) patients remain unknown and are seldom involved in providers’ or payers’ decision-making. Our study aimed to measure preferences and willingness-to-pay (WTP) toward different types of QALY gain for EoL patients with cancer treatment.

METHODS: We attributed QALY gains as four types, gain in LE and QoL, respectively, and during both progression-free survival (PFS) and post-progression survival (PPS). The pilot study was conducted using a discrete choice experiment with 85 Chinese advanced non-small cell lung cancer patients in 2022. Five attributes (the four QALY attributes and one cost attribute) with three levels each, which were set based on actual QALY gain/cost from synthesized results using published data in recent three years, were included. Each respondent answered six choice tasks in a face-to-face interview. The data was analysed using mixed logit models, and heterogeneity was examined using linear regression between individual-level WTPs and demographic characteristics.

RESULTS: Patients valued LE-related QALY gain in PFS most, with a relative importance of 81.97% among all types, and the WTP was $43,162 (95% confidence interval: 26,753-59,572) per QALY gain. Besides, patients generally preferred LE-related QALY gain regardless of disease stage. Heterogeneity was observed in different personal income and educational levels.

CONCLUSIONS: Our findings provide preliminary evidence on the value of different QALY types in EoL stage from a patient perspective and suggest a prioritized resource allocation to those EoL-prolonging health technologies. Given the small sample size and large individual heterogeneity, a full-scale study is recommended to provide more robust results.