The influence of clinical stage, race, and gender on factors which impact quality of life in multiple myeloma.

Abstract

e24126 Background: Multiple myeloma (MM) is unique among hematologic malignancies as an incurable disease. Patients are affected long-term by the disease symptoms as well as psychological, financial burden, and social impact, which may affect overall quality of life (QOL). The current literature related to QOL in MM is largely limited to a single clinical stage, impact concurrent with a specific treatment regimen, or focused on a single QOL factor. Changes in impact on QOL based on longitudinal follow up during the disease course have not been readily assessed. Here, we evaluated patient-reported QOL measures utilized by one time validated questionnaires. Methods: The study enrolled 100 participants in a sequential manner from the Myeloma Clinic at UMGCC with a diagnosis of plasma cell disorders at various stages: MGUS, smoldering myeloma, or multiple myeloma: newly diagnosed, maintenance, relapsed. Participants provided verbal responses to a series of questions listed in Table. Questions aligned with three main domains: physical symptoms and function, mental health, and social systems. The following is an interim analysis of the first 50 patients. Results: This sample of myeloma patients (N=50; males n=26), felt their QOL was impacted by myeloma symptoms (70%). More African American participants reported impact from financial burden (6, 50%) in comparison to Caucasian and other races (10, 26%). Interestingly, males reported less impact on sexual intimacy (3, 15%) than females (6, 43%). Females also reported more impact from financial burden (10, 42%) compared to males (6, 23%). Conclusions: Changes to impact on QOL as a function of clinical MM stage, race, and/or gender will be fully evaluated. Planned analyses include correlation statistics by age and social demographics to determine patterns in patient-reported outcomes. Finally, second interviews with current participants will be conducted to determine changes to impact across the same QOL variables over time.[Table: see text]