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3768 Disparities in Outcomes for Patients with Multiple Myeloma: A SEER Database Analysis

Program: Oral and Poster Abstracts
Session: 907. Outcomes Research: Plasma Cell Disorders: Poster II
Hematology Disease Topics & Pathways:
Research, Clinical Research, Health disparities research, Patient-reported outcomes, Real-world evidence
Sunday, December 8, 2024, 6:00 PM-8:00 PM

Shivani Modi1*, Charishma Bhimineni, DO1* and Mitchell Goldstein, MD2

1Jefferson Einstein Healthcare Network, Norristown, PA
2Jefferson Einstein Healthcare Network, Philadelphia, PA

Background

Multiple myeloma (MM) is a malignancy of plasma cells and is the second most common hematologic malignancy in the United States. There is a significant variability in incidence and outcomes based on racial, socioeconomic, and geographic factors. Understanding these disparities is essential for developing targeted interventions to improve outcomes for all patients with multiple myeloma. This study uses the SEER (Surveillance, Epidemiology, and End Results) database to examine disparities in diagnosis, treatment, and survival outcomes among patients with multiple myeloma, focusing on racial, socioeconomic, and geographic factors. Identifying potential contributing factors to these disparities is crucial for improving health equity in MM care.

Methods

Data Source: The SEER database, which covers approximately 34.6% of the U.S. population, was used for this analysis. Patients with MM diagnosed between 2000 and 2021 were included. The population was stratified by race (White and Black), socioeconomic status (SES) (low, middle, high), and geographic location (urban vs. rural).

Variables Analyzed-Demographic Variables: Age, gender, race, SES, geographic location, stage at diagnosis, treatment modalities (chemotherapy, stem cell transplant), survival outcomes (overall survival, disease-specific survival).

Statistical Analysis: Kaplan-Meier survival analysis was used to compare survival outcomes. Logistic regression was used to analyze factors associated with stage at diagnosis and treatment received.

Results

  1. Racial Disparities

Incidence & Diagnosis-Black patients had an incidence rate of 12.8 per 100,000, compared to 5.6 per 100,000 for White patients. The median age at diagnosis for Black patients was 64 years, compared to 70 years for White patients. 45% of Black patients were diagnosed at an advanced stage (stage III/IV), compared to 30% of White patients.

Treatment- 20% of Black patients received stem cell transplants, compared to 35% of White patients. Only about 50% of Black patients received novel agents (e.g., proteasome inhibitors, immunomodulatory drugs) versus 65% of White patients. Survival-The 5-year overall survival rate was 40% for Black patients, compared to 55% for White patients. After adjusting for stage and treatment, Black patients had a hazard ratio (HR) of 1.25 (95% CI: 1.15-1.36) for overall survival compared to White patients.

  1. Socioeconomic Disparities- Patients from the lowest SES quartile had a 40% advanced-stage diagnosis rate and an 8-month median delay from symptom onset to diagnosis, compared to 25% and 5 months for the highest SES quartile. Lower SES patients had lower rates of stem cell transplants (22% vs. 40%), novel therapeutic agents (45% vs. 70%), and a 5-year survival rate of 38% versus 60%, with an adjusted HR of 1.30 (95% CI: 1.20-1.42).
  1. Geographic Disparities-Patients in rural areas had a 35% advanced-stage diagnosis rate, a 7-month median delay in diagnosis, and lower rates of stem cell transplants (25% vs. 38%) and advanced chemotherapies (50% vs. 68%) compared to urban patients. The 5-year survival rate was 42% for rural patients versus 58% for urban patients, with an adjusted HR of 1.28 (95% CI: 1.18-1.39).

Discussion

The study reveals significant disparities in multiple myeloma diagnosis, treatment, and survival outcomes, with White patients and those in higher socioeconomic statuses or urban areas experiencing earlier diagnoses, more novel treatments, and better survival rates than Black patients and those in lower SES or rural areas. Contributing factors include healthcare access, socioeconomic barriers, and comorbid conditions. To address these issues, we recommend policy interventions to improve access to early diagnosis and treatment, community-based awareness programs, and enhanced healthcare infrastructure in underserved areas, with further research on underlying biological and environmental factors.

Conclusion

This SEER database analysis underscores the need for comprehensive strategies to address disparities in MM outcomes. Ensuring equitable access to diagnosis, treatment, and supportive care is crucial for improving survival and quality of life for all MM patients. Addressing these disparities will require a multifaceted approach involving policy changes, community engagement, and improvements in healthcare delivery systems.

Disclosures: No relevant conflicts of interest to declare.

*signifies non-member of ASH