Chronic Myeloid Leukemia: Impact of Social and Demographic Disparities on Survival Outcomes

Introduction:

Health disparities disproportionately affect minority populations in the United
States across various malignancies. However, the specific impact of race on treatment
accessibility and overall survival in chronic myeloid leukemia (CML) remains inadequately
characterized. This study investigates the influence of racial and ethnic identities and
socioeconomic status on treatment access and survival outcomes in CML patients using the
Surveillance, Epidemiology, and End Results (SEER) database.

Methods:

We conducted a retrospective analysis using SEER data for patients diagnosed with
CML between 2000 and 2021. Demographic and treatment characteristics were compared across
self-identified racial and ethnic groups (White, Black, Asian or Pacific Islander, and American
Indian/Alaska Native). Survival outcomes were assessed using survival time in months and cause
of death. Additional variables included median household income (adjusted for inflation), age,
sex, ethnicity, race, and urbanicity. Chi-squared tests of independence and odds ratios (ORs)
were used to evaluate relationships between these variables and CML outcomes.

Results:

We identified 10,667 patients diagnosed with CML in our analysis of the SEER database. The
racial distribution of the sample was predominantly White (80.51%, N=8,589), followed by
Black (10.84%, N=1,157), Asian or Pacific Islander (7.94%, N=847), and American
Indian/Alaska Native (0.69%, N=74). Regarding ethnicity, the majority identified as non-
Hispanic/Latino (83.68%, N=8,927), while 16.31% (N=1,740) identified as Hispanic/Latino. The
highest incidence of CML was observed in the age groups 50-59 years (20.3%) and 60-69 years
(19.4%), with most patients residing in urban areas with high-income brackets ($90,000+).
Our survival analysis revealed significant disparities across various demographic and
socioeconomic factors. Age played a crucial role, with patients over 80 years showing a
significantly higher risk of cancer-related death compared to the reference group of 10-19 years
(OR: 3.12, 95% CI: 2.76-3.51, p<0.001). Gender also influenced outcomes, with males
exhibiting a slightly poorer survival rate than females (OR: 1.15, 95% CI: 1.04-1.27, p=0.045).
Racial disparities were evident, as White patients demonstrated the best survival outcomes. In
comparison, Asian or Pacific Islander patients had a higher risk of cancer-related death (OR:
1.35, 95% CI: 1.14-1.60, p=0.023), while Black patients showed an even greater risk (OR: 1.55,
95% CI: 1.32-1.82, p=0.018). Other races, including American Indian/Alaska Native, also
exhibited elevated risk (OR: 1.45, 95% CI: 1.25-1.68, p=0.018).
Socioeconomic status emerged as a significant factor influencing survival outcomes. Patients in
high-income brackets (>$100,000) had the best survival rates. Those in middle-income brackets
($50,000-$100,000) showed an increased risk of cancer-related death (OR: 1.75, 95% CI: 1.55-
1.98, p<0.001), while low-income patients (<$50,000) faced the highest risk (OR: 2.05, 95% CI:
1.83-2.30, p<0.001). Interestingly, when adjusted for other variables, ethnicity showed minimal
impact on survival (OR: 1.05, 95% CI: 0.95-1.16, p=0.317), suggesting that other factors may
play a more significant role in determining CML outcomes than ethnic background alone.

Conclusion:

Our analysis of CML outcomes using SEER data reveals persistent disparities across
demographic and socioeconomic lines, highlighting the complex interplay between social
determinants of health and clinical outcomes. The pronounced differences in survival rates
among racial groups and socioeconomic strata suggest significant variations in access to
specialized care, treatment adherence, and overall healthcare quality. The impact of advanced age
on CML outcomes underscores the unique challenges in managing this disease in elderly
populations. Interestingly, the minimal impact of ethnicity when adjusted for other variables
suggests that socioeconomic factors may play a more crucial role in determining CML outcomes
than ethnic background alone.