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Simon Fifer,1 Jayne Galinsky,2 Sarah Richard3 1Community and Patient Preference Research (CaPPRe), Sydney, NSW, Australia; 2Myeloma UK, Edinburgh, Scotland; 3PRMA, Edinburgh, ScotlandCorrespondence: Simon FiferCommunity and Patient Preference Research (CaPPRe), Sydney, NSW, AustraliaTel +61 403 862 091Email simon.fifer@cappre.com.auBackground: Myeloma is an incurable life-threatening hematological cancer. Recent treatment developments have seen improvements in survival; however, while patients are living longer, they are living with symptoms and treatment side effects.Objective: To evaluate myeloma patients’ preferences for treatment using a discrete choice experiment (DCE). This study set out to define the relative importance of key treatment attributes, characterize the risk-benefit trade-offs in patients’ decision-making, and to analyze the predictive power of basic demographic factors.Methods: Four hundred seventy-five myeloma patients in the UK were invited to participate by Myeloma UK. Data were collected using DCEs through an online survey. The DCEs presented patients with 10 choice scenarios, each with 2 treatment options described by 7 attributes, and a “no treatment” option. The DCE data were modelled using a latent class model (LCM). The effects of demographic characteristics were also examined.Results: Not surprisingly, average survival was most important to all patients but there were significant contrasts between the class preferences. The LCM revealed two classes of patients. Patients in Class 1 placed greater importance on average survival and mild-to-moderate side effects, whereas patients in Class 2 focused on the mode of administration and the average out-of-pocket costs. Patients living with others and those diagnosed in the last 5 years were more likely to be in Class 1.Conclusion: Different treatment features were not valued equally among all myeloma patients. This has important implications for healthcare policy decisions and could be used to guide decisions around the value of new myeloma medicines.Keywords: discrete choice experiment, patient preferences, myeloma, health technology assessment, dashboards