Race and Ethnicity As a Category Poses Challenges in Global Registries: Experience from the Waustim Project of the Worldwide Network for Blood and Marrow Transplantation, WBMT

Introduction The terms race and ethnicity (often synonymous) pose challenges in clinical research. Race is a social construct based on visible physical characteristics and ethnicity encompasses shared cultural, linguistic, and ancestral characteristics but neither are biological constructs. These terms reflect historical and social contexts that contribute to health disparities and can lead to misattribution of outcomes, potentially obscuring biological variables in disease or pharmacogenomics and other social determinants of health. This abstract demonstrates the limitations of these categories, as exemplified in the Worldwide Network for Blood and Marrow Transplantation, Waustim global registry study on newly diagnosed multiple myeloma (NDMM) patients undergoing autologous stem cell transplantation and highlights the need for clarity in these terms. Methods Contributions from the European Society for Blood and Marrow Transplantation, Center for International Blood and Marrow Transplantation, and Asian Pacific Blood and Marrow Transplant Group were included. The term race is used in the US and ethnicity is used in the UK. Two cohorts were analyzed: patients categorized as “Black” in the US (African, African-American, Black Caribbean, Black South or Central American or other Black) and UK (African, Caribbean or other Black background) and patients categorised as “Asian” from the US (South Asian, Filipino, Japanese, Korean, Chinese, Vietnamese and other Southeast Asian), UK (South Asian heritage: India, Pakistan, Bangladesh, Sri Lanka and other origins or East Asian heritage: China, Hong Kong, Taiwan, Chinese Malaysian, Japan, Korea and other origins) and the Asia region (Japan, Malaysia, Taiwan) where it was assumed all those transplanted are “Asian.” Endpoints included overall survival (OS), progression-free survival (PFS), relapse incidence (RI) and non-relapse mortality (NRM). Statistical analyses included the Kaplan-Meier estimator, log-rank test, and Cox proportional hazards model. Results Of 61,725 patients with NDMM, 2,923 were categorized as “Black.” There were no significant differences in age, sex, MM subclassification, ISS stage, high-risk cytogenetics, and remission status between patients in the US and UK. However, there were differences in baseline characteristics, such as the Karnofsky score, where the UK had a higher proportion of patients with a score ≤90 (72.1% vs. 51%) and the US had a higher proportion of patients with an HCT-CI of ≥3 (48.2% vs. 11.6 %). Given these differences, it appears that the category of “Black” was not analogous between the two countries. Despite this, multivariate analysis did not show differences in OS, PFS, RI, and NRM. In the “Asian” cohort, data from Japan (n=3113), Taiwan (n=524), Malaysia (n=169), the US (n=327), and the UK (n=192) showed significant differences in MM subclassification, high-risk cytogenetics, and Karnofsky scores. Multivariate analysis showed a lower OS in patients from Malaysia [HR 1.65 [95% CI 1.13-2.41], p=0.01], Taiwan [1.47 [95% CI 1.14-1.89], p=0.003], and the UK [1.51 [95% CI 1.02-2.24], p=0.04] than in patients from Japan [HR 1.0] and the US [HR 0.66 [95% CI 0.46-0.95], p=0.02]. Compared to patients in Japan, PFS was significantly lower in Malaysia (HR 1.56 [95% CI 1.19-2.06], p=0.002), Taiwan (HR 1.21 [95% CI 1.01-1.45], p=0.04), and the UK (HR 1.38 [95% CI 1.05 -1.82], p=0.02), likely related to differences in RI. Given the heterogeneity of outcomes, “Asian” appears to be inadequate for classifying such a large and diverse population. Conclusion These findings underscore the limitations of using “race/ethnicity” as a category in registries worldwide, and the need for a more contemporary understanding of the term. For instance, the term “Asian” essentially covers half of the global community but is defined differently in the US and the UK, and the population compositions vary between the two countries. Our experience demonstrates that these broad classifications do not apply universally and can obscure critical differences among patient populations. Future research should focus on more specific and meaningful classifications that capture social determinants of health beyond race/ethnicity, which are known to influence healthcare outcomes and pharmacogenomic data where relevant, to improve the applicability and equity of clinical data.

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