Characterizing Cancer Burden in the American Indian Population in North Carolina.

BACKGROUND: The American Indian (AI) population in North Carolina has limited access to the Indian Health Service. Consequently, cancer burden and disparities may differ from national estimates. We describe the AI cancer population and examine AI-White disparities in cancer incidence and mortality. METHODS: We identified cancer cases diagnosed among adult AI and White populations between 2014 and 2018 from the North Carolina Central Cancer Registry. We estimated incidence and mortality rate ratios (IRR and MRR) by race. In addition, between the AI and White populations, we estimated the ratio of relative frequency differences [RRF, with 95% confidence limits (CL)] of clinical and sociodemographic characteristics. Finally, we evaluated the geographic distribution of incident diagnoses among AI populations. RESULTS: Our analytic sample included 2,161 AI and 204,613 White individuals with cancer. Compared with the White population, the AI population was more likely to live in rural areas (48% vs. 25%; RRF, 1.89; 95% CL, 1.81-1.97) and to have Medicaid (18% vs. 7%; RRF, 2.49; 95% CL, 2.27-2.71). Among the AI population, the highest age-standardized incidence rates were female breast, followed by prostate and lung and bronchus. Liver cancer incidence was significantly higher among the AI population than White population (IRR, 1.27; 95% CL, 1.01-1.59). AI patients had higher mortality rates for prostate (MRR, 1.72; CL, 1.09-2.70), stomach (MRR, 1.82; 95% CL, 1.15-2.86), and liver (MRR, 1.70; 95% CL, 1.25-2.33) cancers compared with White patients. CONCLUSIONS: To reduce prostate, stomach, and liver cancer disparities among AI populations in North Carolina, multi-modal interventions targeting risk factors and increasing screening and treatment are needed. IMPACT: This study identifies cancer disparities that can inform targeted interventions to improve outcomes among AI populations in North Carolina.

Health Care Access Dimensions and Racial Disparities in End-of-Life Care Quality among Patients with Ovarian Cancer.

This study investigated the association between health care access (HCA) dimensions and racial disparities in end-of-life (EOL) care quality among non-Hispanic Black (NHB), non-Hispanic White (NHW), and Hispanic patients with ovarian cancer. This retrospective cohort study used the Surveillance, Epidemiology, and End Results-linked Medicare data for women diagnosed with ovarian cancer from 2008 to 2015, ages 65 years and older. Health care affordability, accessibility, and availability measures were assessed at the census tract or regional levels, and associations between these measures and quality of EOL care were examined using multivariable-adjusted regression models, as appropriate. The final sample included 4,646 women [mean age (SD), 77.5 (7.0) years]; 87.4% NHW, 6.9% NHB, and 5.7% Hispanic. In the multivariable-adjusted models, affordability was associated with a decreased risk of intensive care unit stay [adjusted relative risk (aRR) 0.90, 95% confidence interval (CI): 0.83-0.98] and in-hospital death (aRR 0.91, 95% CI: 0.84-0.98). After adjustment for HCA dimensions, NHB patients had lower-quality EOL care compared with NHW patients, defined as: increased risk of hospitalization in the last 30 days of life (aRR 1.16, 95% CI: 1.03-1.30), no hospice care (aRR 1.23, 95% CI: 1.04-1.44), in-hospital death (aRR 1.27, 95% CI: 1.03-1.57), and higher counts of poor-quality EOL care outcomes (count ratio:1.19, 95% CI: 1.04-1.36). HCA dimensions were strong predictors of EOL care quality; however, racial disparities persisted, suggesting that additional drivers of these disparities remain to be identified. SIGNIFICANCE: Among patients with ovarian cancer, Black patients had lower-quality EOL care, even after adjusting for three structural barriers to HCA, namely affordability, availability, and accessibility. This suggests an important need to investigate the roles of yet unexplored barriers to HCA such as accommodation and acceptability, as drivers of poor-quality EOL care among Black patients with ovarian cancer.