Abstract
e20036 Background: Multiple myeloma is an aggressive monoclonal plasma cell proliferative disorder that is the second most common hematologic malignancy. On a global scale, multiple myeloma led to an estimated 106,000 deaths in 2018 alone. The exact cause of multiple myeloma is not well understood. Later stage of diagnosis is correlated with worse outcomes; thus, it is critical to assess the socioeconomic factors associated with diagnosis at early versus late stages. Methods: Using the National Cancer Database, we aimed to identify associations between socioeconomic factors of patients that present with Revised International Staging System (R-ISS) stage I multiple myeloma in comparison to R-ISS stage III at diagnosis. In this study, 5,512 patients from the National Cancer Database who were diagnosed with R-ISS stage I and stage III multiple myeloma were analyzed based on age, ethnicity, race, education, insurance type, income, education, geographic location, facility type, sex, Charlson-Deyo score, and urban or rural setting. Demographic factors of patients that presented with stage I and stage III disease were analyzed using chi square, ANOVA, and multivariate analyses. All patients included in the study were diagnosed with multiple myeloma between 2004 and 2020. Results: We identified significant (P < 0.05) associations between insurance type, median income, education, rural setting, and Charlson-Deyo score with diagnosis of R-ISS stage III multiple myeloma. For insurance type, private insurance, other government insurance, and Medicaid had lower percentages of R-ISS stage III diagnosis than patients without insurance (P < 0.001). Medicaid and over government insurance were up to 70% less likely to present with stage III MM than patients without insurance (P < 0.001). Regarding income and education, patients from a zip-code associated with an income of < $38,000 and zip-codes with lower levels of high school diploma had higher rates of stage III multiple myeloma diagnosis (P < 0.001). Patients from completely rural or less than 2,500 urban population adjacent to a metro area (P < 0.005) and not adjacent to a metro area (P < 0.025) showed significant increase in later stage multiple myeloma diagnosis than those from a metro setting with population above one million. Patients with Stage III at presentation were older than patients with stage I on average (P < 0.001). There were no significant differences seen based on race, sex, ethnicity, or region in the United States. Conclusions: Factors associated with increased likelihood of later stages of diagnosis of multiple myeloma include insurance type, median income, education, and rural location. Future analysis should further investigate the specific barriers to early patient diagnosis and treatment due to insurance type, education level, and rural setting.