ASPO Abstracts
Characterizing the cancer burden in American Indian populations in North Carolina
Category: Cancer Health Disparities
Conference Year: 2023
Abstract Body:
Purpose: North Carolina (NC) has the largest American Indian (AI) population in the eastern US. Despite cancer being the second leading cause of death among AI in NC, limited information is available on cancer incidence and mortality among this population. To fill this gap, we used a population-based sample to: 1) describe the AI population diagnosed with cancer; and, 2) examine the differences in cancer incidence and mortality between AI and White populations. Methods: We identified all cancer cases diagnosed among NC adult AI and White populations between 2003 and 2018 using the Cancer Information and Population Health Resource (CIPHR), which includes data from the NC Central Cancer Registry (NCCCR). We compared characteristic differences between the AI and White populations using ratios of relative frequency (RRF), and estimated incidence and mortality rates age-adjusted to the 2000 US standard population. Results: Our population-based analytic sample included 5,405 AI and 565,170 White individuals. Compared to the White cancer population, AIs were more likely to live in rural areas (50% vs 26%; RRF=1.92), to receive Medicaid (19.4% vs 6.9%; RRF=2.78), and to be diagnosed at a younger age (median: 62 vs 66 years). In terms of stage at presentation, AI were less frequently diagnosed in situ (1.9% vs 3.4%; RRF=0.57) or localized (41.6% vs 44.9%; RRF=0.93) and more frequently diagnosed with regional (22.4% vs 20.6%; RRF=1.09) and distant stage (25.9% vs 23.5%; RRF=1.11). The most frequently diagnosed cancers among the AI population were lung and bronchus, prostate, female breast, colorectal, and kidney. Compared to the White population, there was a higher incidence rate (per 100,000 persons) among AI populations for stomach (5.8 vs 5.1) and liver (7.8 vs 6.5). In terms of mortality, AI populations had a higher mortality rate (per 100,000) for prostate (11.8 vs 8.3), stomach (3.0 vs 2.2), and liver cancer (4.0 vs 3.5). Conclusion: This study identifies the most substantial AI disparities in cancer outcomes and provides guidance on where to target interventions to improve cancer outcomes among AI populations. Nevertheless, these estimates may underestimate the magnitudes of disparities given the known misclassification of AI in cancer registry data.
Keywords: American Indian, outcome disparities, cancer burden