A discrete choice experiment analysis to understand patient preferences for multiple myeloma treatments

Multiple myeloma (MM) is a malignant plasma cell disorder characterized by the clonal expansion of abnormal plasma cells within the bone marrow. The management of relapsed/refractory multiple myeloma (RRMM) represents a significant challenge as the disease relapses or becomes refractory to previous treatments. Recent advances in therapy have expanded RRMM treatment options. This study aimed to gain a deeper understanding of patients' treatment preferences regarding available therapeutic options.

This study was designed as a non-interventional descriptive cross-sectional study based on an online discrete choice experiment (DCE) among adult RRMM patients living in the between USA November 2023 and March 2024. The survey included attributes and levels derived from an extensive literature review and guided interviews conducted with MM patients. Preference data were analyzed using a conditional logistic (CL) regression model and relative attribute importance (RAI) scores were calculated. Patients' willingness to trade off overall response rate (ORR) was evaluated using the partworth utilities estimated from the CL model.

149 MM patients completed the survey; 66% had received 1-2 prior lines of therapy, 15% three prior lines, 19% four or more prior lines. Patients significantly preferred treatments with longer progression-free survival (PFS) and overall survival (OS) and higher ORR (RAI: 36.4% and 22.1%, respectively). With respect to adverse events assessed in this study, patients expressed concern for cytokine release syndrome (CRS) (RAI: 15.2%) and infections (RAI: 11.9%). In contrast, nail/skin disorders, duration of hospitalization, and taste disorder were less important to patients. Patients would be willing to accept a high risk of CRS (72% over no risk) to gain 29% increase in ORR.

Patients showed a clear preference for treatment efficacy (PFS/OS and ORR). This study confirmed patients' valuation on treatment attributes in the new treatment landscape and highlighted the importance of shared treatment decision-making for optimal clinical outcomes.