Racial Differences in Multiple Myeloma Survival and Treatment Using Pooled Clinical Trial and Real-World Electronic Medical Record Data

Background: Past studies have indicated a potential racial disparity in Multiple Myeloma (MM) survival between black and white patients (Costa et al., 2017; Marinac et al., 2020), an issue compounded by minority underrepresentation in clinical trials (Ailawadhi et al., 2018). To better understand how racial disparities affect both MM survival and access to treatment, we performed an analysis of pooled clinical trial (CT) and Real-World EMR Data (RWD). Methods: Eligible Phase II and III open-label MM clinical trials were identified from the Medidata Enterprise Data Store, which comprises over 22,000 historical clinical trials, for de-identified aggregate analyses. De-identified Oncology RWD was sourced from the Guardian Research Network of integrated delivery systems from 2016 to 2020. Baseline characteristics were analyzed in both cohorts. Race was categorized as black, white, or other. Overall Survival (OS) was assessed using Kaplan-Meier analysis. In the RWD, therapy utilization was assessed by race. Results: The RWD contained 5871 patients, with 17.5% black, 78.3% white, and 4.2% other race. Median age in years at diagnosis was 69 for blacks, 72 for whites, and 70 for other races. The gender breakdown was 54.2% female in blacks, 46.0% in whites, 45.9% in those of other races respectively. Median number of prior regimens was 2, with no differences between racial groups. The CT data contained 851 patients, with 1.4% black, 93.5% white, and 5.1% other race. Median age in years at diagnosis was 62 for blacks, 58 for whites, and 55 for other races. The gender breakdown was 33.3% female in blacks, 43.5% in whites, and 46.7% in those of other races respectively. Median number of prior regimens was 5, with no differences between racial groups. There was no statistically significant difference in OS between racial groups in either dataset. In the CT data with median follow-up of 7.8 years, survival from date of diagnosis to last visit or date of death was 25% for blacks and 18% for whites. Currently, in the RWD, 3-year survival comparing blacks to whites is 85% to 83%. The proportion of treated RWD patients appears to be similar between black and white patient groups, with 56% of white and 53% of black patients receiving 1st line therapy, and 33% and 31% receiving 2nd line therapy, respectively. Among newer therapy modalities, white patients had a higher utilization of targeted antibody agent daratumumab (8.7% utilization among whites, 5.2% in blacks, p Conclusions: Though there were no demonstrated differences in survival between racial groups in either dataset, the RWD suggested differences in treatment utilization, with underutilization of novel therapies like proteasome inhibitors and targeted antibody therapy and later treatment initiation in blacks. Previous studies (Fiala et al., 2017) have noted similar trends, which suggest that therapeutic advances may not be equitably available to all racial groups. This observation could not be replicated in CT data, but merits further exploration. Despite black patients making up 17.5% of patients in the RWD, a racial distribution consistent with published literature (Rosenberg et al., 2015), black patients made up only 1.3% of patients in the CT data. Furthermore, in the CT data, the median age of black patients was older than that of the white and other race groups (62 years compared to 58 and 55, respectively). This observation is magnified by evidence in both the RWD and other datasets (Fillmore et al., 2019) that shows a younger age of onset in black MM patients. Given the strong correlation between age and poorer outcomes in MM (Ludwig et al.,2008), it is possible that these clinical trials are not capturing a representative black patient population, and results may not be generalizable to other groups. Recruitment of black patients should remain a priority in clinical studies in order to effectively assess racial disparities in MM treatment access and survival. Disclosures Rusli: Acorn AI by Medidata, a Dassault Systemes Company: Current Employment, Current equity holder in publicly-traded company. Diao: Acorn AI by Medidata, a Dassault Systemes Company: Current Employment. Liu: Acorn AI by Medidata, a Dassault Systemes Company: Current Employment. Kelkar: Acorn AI by Medidata, a Dassault Systemes Company: Current Employment. Ensign: Acorn AI by Medidata, a Dassault Systemes Company: Current Employment, Current equity holder in publicly-traded company. Watson: Guardian Research Network, Inc.: Current Employment. Galaznik: Acorn AI by Medidata, a Dassault Systemes Company: Current Employment, Current equity holder in publicly-traded company.