Assessment of differences in demographic characteristics and clinical diagnoses among black and white oncology patients with COVID

Bhandari, S.; Mueller, J.; Whyte, W.; Heilbroner, S. P.

Background: Health disparities between black and white COVID-positive patients are well documented. To help address these disparities, clinicians need to understand the specific health challenges faced by black COVID patients compared to their white counterparts. These challenges are understudied in the oncologic setting. Hence, we present the demographic and clinical features of black COVID-positive cancer patients compared to whites. Methods: We used ConcertAI's database of oncology EMR data, which includes clinical data from CancerLinQ Discovery. We conducted twosample t-tests and chi-squared tests to measure the differences in black and white COVIDpositive cancer patients across age, gender, ethnicity, state, region, ECOG, BMI, all cancer indications, stage, and Charlson comorbidities. COVID positivity was defined using claims data. Only relevant significant results are reported to save space. Results: Table summarizes the differences in 429 black and 980 white cancer patients with COVID. Black patients were younger, more likely to have an elevated BMI, and have a higher prevalence of breast cancer, congestive heart failure, diabetes, multiple myeloma, peptic ulcer disease, and renal disease. They also had less melanoma. Results were statistically significant at 0.05 level. Analyzing only black patients by COVID status shows very similar results. Conclusions: Black cancer patients suffer from multiple comorbid conditions that increase their risk of adverse outcomes when infected with COVID-19. The CDC lists eight comorbidities that put patients at a higher risk of severe COVID infection. Black patients in our cohort have a higher prevalence of four out of eight of these conditions- elevated BMI, renal disease, congestive heart failure, and diabetes. Clinicians should inspect for these comorbidities while treating this atrisk population. Demographic and clinical characteristics of patients.