Multiple Myeloma Transplant: Examining the Intersection of Access, Age and Race

Introduction: Autologous Stem Cell Transplant (ASCT) is standard frontline therapy for patients newly diagnosed with Multiple myeloma (MM). Receipt of ASCT is influenced by factors such as race, age, socioeconomic status (SES), and geographic location. The degree to which these factors collectively influence MM transplant access and jointly impact overall survival is not well established. Our study aimed to assess the impact of age, race, rurality, and area-level SES on ASCT transplant receipt and overall survival following MM diagnosis.

Methods: An IRB approved retrospective analysis was conducted of adult MM patients diagnosed in 1992-2020 from The Ohio State University Comprehensive Cancer Center (OSUCCC). Patients included were previously consented to the Buckeye Surveillance, Contact, and Research for Multiple Myeloma and Amyloidosis Protocol (NCT01408225); a registry database for patients with suspected plasma cell dyscrasia pursuing care at OSUCCC; and the Bone Marrow Transplant (BMT) registry, an internal database compiled of demographic and transplant-specific data. Area-level SES was measured by census tract-level (2008-2017) Yost indices (a composite of education-, income-, and occupation-related variables.)^{1, 2} Rural-urban status was measured by census tract-level 2010 Rural-Urban Commuting Area (RUCA) codes.³ Yost were categorized into quartiles where higher quartiles represented higher SES, and RUCA codes were grouped by metropolitan (Primary RUCA 1-3) v. non-metropolitan (Primary RUCA 4-10). Poisson regression models with robust variance were used to evaluate the associations between patient characteristics and receipt of transplant. Overall survival (OS) from diagnosis was analyzed and median OS was estimated using the Kaplan-Meier method. Cox proportional hazard models were used to estimate the hazard ratios of risk of death.

Results: In the combined MM registries, a total of 1,799 MM patients were included in this analysis, 1,169 (65%) received a transplant. MM patients median age at diagnosis was 61 (17-87), race was self-identified as White (85.6%), Black (13.1%) other (1.3%). In multivariable analysis, patients who were 65 years or older were less likely to undergo a transplant (age 65-70: IRR=0.80, 95% CI: 0.72-0.89, p<0.001; age > 70: IRR 0.23, 95% CI: 0.18-0.30, p<0.001). When assessed by race, relative to White patients, Black patients were less likely to receive a MM transplant (IRR=0.85, 95% CI: 0.74-0.97, p=0.018). RUCA code showed no significant difference in receiving a transplant between the non-metropolitan v. metropolitan groupings (IRR 1.06, 95% CI: 0.97-1.16, p=0.186). Residence in higher SES areas (quartiles 2-4) was associated with higher rate of ASCT receipt compared to those in quartile 1 (IRR 1.16, 95% CI: 1.05-1.29, p=0.038).

Among all MM patients median OS for age <65 was 9.0 years (95%CI 8.4-9.7); age 65-70, 7.0 years (95%CI 6.3-7.9); age>70, 4.7 years (95%CI 4.0-5.3). In multivariable analysis, hazard of death was lower for those who received a transplant (vs. no transplant, HR= 0.63, 95%CI 0.53-0.74, p<0.001), patients identified as Black (vs. White, HR=0.66, 95%CI 0.51-0.85, p=0.001), and those residing in higher SES areas (quartile 2-4 vs. quartile 1, HR=0.69, 95%CI 0.58-0.83, p<0.001). Advancing age was associated with higher hazard of death, age 65-70 HR=1.45 (95%CI 1.18-1.78, p<0.001); age >70 HR=2.03 (95%CI 1.65-2.49, p<0.001). Rurality was not associated with OS (HR 1.14, 95% CI 0.96-1.35, p=0.134).

Conclusions: In a large MM population, age, race, and area-level socioeconomic status impact both the receipt of transplant and overall survival following MM diagnosis. Area-level SES could be an important driver of MM survival independent of transplant access.

Rosko:Genentech: Research Funding; Pfizer: Research Funding; Merck Foundation: Research Funding. Jaglowski:Gamida: Consultancy; Kite: Consultancy, Research Funding; Novartis: Research Funding; CRISPR Therapeutics: Consultancy. Khan:Secura Bio: Consultancy, Research Funding; Amgen: Speakers Bureau; Janssen: Honoraria; Sanofi: Speakers Bureau. Bumma:Amgen: Consultancy, Speakers Bureau; Sanofi, Genzyme: Other: Ad Board, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Other: Ad Board.