OBJECTIVES Value-of-Information analysis can help to guide decision about future research priorities: If and what further research is needed? Our aim was to guide decision regarding future outcomes research on parameters related to different regimens for chronic myeloid leukemia (CML). METHODS We updated a previously developed state-transition Markov model of CML, which evaluates seven treatment regimens including tyrosine kinase inhibitors, chemotherapy and stem cell transplantation (SCT). We derived model parameters from published trials data, Austrian clinical, epidemiological, and economic data. We performed a cohort simulation over a lifetime horizon, adopted a societal perspective, and discounted costs and benefits at 3% annually. We calculated the expected value of perfect information (EVPI), partial perfect information (EVPPI), and the population EVPI (PEVPI). Additionally, we examined the expected value of sample information (EVSI) for different trial sizes. RESULTS Three strategies are on the efficiency frontier: imatinibàchemotherapy/SCT, nilotinibàchemotherapy/SCT (140,000 €/QALY) and nilotinibàdasatinibàchemotherapy/SCT (176,000 €/QALY). The EVPI for eliminating all uncertainty resulted in a curve with two peaks. One peak is around a WTP threshold of 150,000 €/QALY (EVPI 4,600 €) and another peak is at 180,000 €/QALY ( EVPI 7,700 €). The PEVPI for Austria assuming a 10-year technology horizon was 2.5 million € (WTP 150,000 €/QALY) and 4.5 million € (WTP 180,000 €/QALY). EVPPI identified four parameters most responsible for decision uncertainty: duration of first-line therapy, probability of progressing from chronic phase to accelerated phase, probability of receiving a SCT, and the health-utility after SCT. The EVSI commented on the optimal study size for these parameters given the cost of obtaining information. CONCLUSIONS Acquiring additional evidence could prove valuable for determining optimal treatment regimens for chronic myeloid leukemia. If further research were funded, studies should examine a combination of natural history, treatment, and quality of life parameters, especially the effectiveness of first-line TKI treatment.