Abstract
Multiple myeloma (MM) remains an incurable malignancy characterized by plasma cells that are nurtured and proliferate within the permissive bone marrow milieu. It has a greater incidence in African Americans (AA) compared to whites (13.8 vs. 6.5/100,000). The five-year age adjusted mortality rate, according to SEER database, is greater in AA compared to white Pts (5.8 vs. 2.9/100,000), which is likely explained by a greater incidence in the AA population. However, recent reports have also shown that AAs with equal access to care have an even better survival than their white counterparts [Fiala et al. Cancer. 2017]. Conversely, results from the CoMMpass registry database showed that OS was shorter for AA compared with Whites (age-adjusted hazard ratio (HR) 1.7, 95% confidence interval 1.2-2.4, P = 0.003) [Derman et al. Blood Cancer J. 2020]. Here, we report the interplay of race and other dimensions of MM care using the National Cancer Database (NCDB).
Methods: NCDB is the largest cancer database in the US including >70% of all newly diagnosed cancer patients. The International Classification of Diseases for Oncology (ICD-O) code of 9732 was used. OS was calculated from the date of MM diagnosis. Given that Smoldering MM (SMM) does not have specific ICD code, we defined patients who did not receive any treatment within 3 months after the diagnosis as SMM, similar to other authors (Ravindran et al. Blood Cancer J. 2016). Initiation of systemic treatment was considered as a surrogate of progression to symptomatic MM. Overall survival (OS) of SMM patients was calculated from initiation of systemic treatment after they progressed to MM, estimated by the Kaplan-Meier method, and compared with the log-rank test. Cumulative incidence of progression from SM to MM was calculated with death as a competing risk and compared with the Gray's test. Multivariable Cox and logistic regression analysis were performed to identify independent predictors of OS and progression to MM, respectively.
Results: We identified 56,021 patients with MM and 11,485 with SMM between 2010 to 2014 in this database. Among MM patients, 42,836 (76%) were white and 11,255 (20%) self-identified as AA. For AA patients, there was a lower proportion of Medicare (46 vs. 56%), and private insurance (35 vs. 36%) and a higher percentage of Medicaid (11 vs. 5%) and uninsured Pts (6 vs. 3%) compared to Pts that self-identified as white. A larger proportion of AAs had a Charlson score ≥1 (30 vs. 24%, p<0.001). The percentage of Pts who underwent radiation was higher among whites compared to AA (23 vs 8%). However, unadjusted OS was greater for AA compared to white Pts, 55 vs. 48 months, respectively (P < 0.0001). Among SMM patients, 8,324 (72%) were white and 2,756 (24%) were AA. SMM was diagnosed in AA patients at a median of 3.7 years younger than in white patients. Similar socioeconomic disparities were observed in SMM as in MM cohort. The time from diagnosis of SMM to first therapy which is indicative of progression from SMM to MM is the same among AA and white (median time in days 136 vs 135 days, p=0.672) with comparable OS. Multivariable Cox and logistic regression analysis showed that lower age, AA race, Female gender, ASCT, living in a higher income area and having Medicare or Private insurance compared to no insurance were independent predictors for better OS in MM. Although other predictive factors persisted for patients with SMM, race did not reach statistical significance.
Conclusion: Taken together, our results utilizing one of the largest available datasets in the US, reflect a similar outcome for AA and white patients with MM despite a clear disparity in healthcare access and SES. This finding might suggest a more favorable biology of the disease among AA Pts. The lower rate of radiation among AA is also an indirect measure of bone complications. AA enjoy less bone loss and fractures under physiologic and pathologic conditions. Further studies to elucidate the role of bony compartment of the MM microenvironment at the cellular and molecular levels might be able to explain this disparity and help advance a more personalized treatment options to improve outcomes.
Disclosures
Metheny:Incyte: Speakers Bureau; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Gamida: Membership on an entity's Board of Directors or advisory committees. Malek:Sanofi: Consultancy; Takeda: Consultancy, Speakers Bureau; AdaptiveBio: Consultancy, Honoraria; Amgen: Speakers Bureau; BMS: Speakers Bureau; janssen: Consultancy; GSK: Speakers Bureau; Karyopharm: Consultancy, Speakers Bureau.
