OBJECTIVES: Since the launch of Imatinib, the survival of chronic myeloid leukemia (CML) has significantly improved, but also caused enormous increase in long-term costs of CML care. Neither health-related utility of CML patients nor long-term cost-effectiveness of imatinib, however, has been investigated in Taiwan. This feasibility study aims to explore the applicableness of time-trade-off (TTO) to measure utility of CML patients treated with imatinib. METHODS: This cross-sectional study was conducted at a medical center in southern Taiwan from June 2011 to January 2012. Outpatients with defined diagnosis of CML and receiving imatinib were invited to participate. After TTO measurement, semi-structure interviews were conducted to explore participates' perceptions. The interviews were audiotaped, transcribed verbatim and analyzed by constant comparison untill saturation. RESULTS: Of all, 22 (mean age: 52.4±15.83 years, male: 63.6%) of the 24 participants completed the study. The average utility was 0.774±0.219. Most participants accepted current health status and life expectancy, and considered current health status is not different from ideal situation. Mid-age participants traded off life span with parenting duty, while the elderly considered companion time with their partners. For those who chose shorter life span with better health, the main concern was financial burden to family because the disease-related fatigue constrained activity and work ability. In addition, regular medical treatment was also considered by those who desired better career paths, long-term traveling and those consisting of multi-comorbidity. Moreover, uncertainty about future, limited social support and financial difficulty were also the reasons for trading off. CONCLUSIONS: TTO is applicable to measure utility for CML patients. Participants receiving  imatinib generally presented satisfactory health status and trading remaining years of life with other concerns. To validate this tool, further studies need to explore utilities of patients with disease symptoms or drug-related side effects, and compare the results with disease-specific measures.