Racial and Ethnic Differences in the Utilization of Autologous Transplantation for Lymphoma in the United States

BACKGROUND: Racial/ethnic disparities in the utilization of hematopoietic cell transplantation (HCT) have been reported for patients with hematologic malignancies, but population-based data are lacking for lymphoma patients. The objective of this study was to determine whether racial and ethnic disparities exist in the utilization of autologous HCT for lymphoma in the United States.

METHOD: We used Surveillance, Epidemiology, and End Results data linked to Medicare fee-for-service claims. We included Medicare beneficiaries aged 66+ years with Hodgkin or Non-Hodgkin lymphomas diagnosed between 2008 and 2015. The primary outcome was time-to-autologous HCT. We used Cox proportional hazards models to estimate racial/ethnic differences in utilization. Missing data were handled using multiple imputation with chained equations.

RESULTS: We included 40,605 individuals with lymphoma. A total of 452 autologous transplants were performed. In the unadjusted model, Non-Hispanic Black patients were 51% less likely to receive a transplant than Non-Hispanic White patients (95% CI, 0.26-0.96; p = 0.04). After adjusting for age at diagnosis and sex, Non-Hispanic Black patients were 61% less likely to receive a transplant (95% CI, 0.20-0.76; p = 0.01). However, observed differences attenuated and became non-significant after adjustment for socioeconomic factors (adjusted hazard ratio [aHR], 0.62; 95% CI, 0.32-1.21; p = 0.16) and disease-specific factors (aHR, 0.58; 95% CI, 0.30-1.12; p = 0.11), separately. In the fully adjusted model, we also did not observe a statistically significant association between Non-Hispanic Black race/ethnicity and receipt of transplant (aHR, 0.54; 95% CI, 0.28-1.05; p = 0.07).

CONCLUSION: In this population-based cohort study of lymphoma patients, Non-Hispanic Black patients were less likely to receive autologous HCT compared to Non-Hispanic White patients, but this difference was partially explained by socioeconomic and disease-specific factors.