Geographical and Racial Disparities in Head and Neck Cancer Diagnosis in South-Eastern United States: Using Real-World Electronic Medical Records Data

Abstract

Background: Rurality, race, and age at diagnosis are important predictors in head and neck cancer (HNC) prognosis. However, literature on the associations of rurality and race with age at HNC diagnosis is limited. Data on geographical, racial, and gender disparities in young HNC patients (diagnosed £ 45 years) are also scarce. Materials and Methods: This retrospective study assesses rural-urban, racial, and gender disparities in age at HNC diagnosis, using electronic medical records (Cerner) data of 4258 HNC patients (1538 residing in rural counties and 2720 in urban counties) from National Cancer Institute-designated cancer center in Alabama. Rurality was defined based on 2010 U.S. Census Bureau's rural-urban classification. Logistic regression was used to assess the association of young HNC diagnosis with demographical, behavioral, and clinical variables. ArcGIS 10.2 was used to map geospatial distribution of age and population-adjusted HNC case across rural and urban counties. Results: Patients from rural counties were less likely to be diagnosed at younger age (£ 45 years) compared with urban counties (odds ratio [OR] [95% confidence interval (CI)]: 0.74 [0.58-0.93]). Most patients present at stage III/IV (64.9% in rural and 60.2% in urban). Compared with white patients, black patients were 70% more likely to get diagnosed at a young age (95% CI: 1.23-2.35). Young patients were more likely to be females and blacks compared with older patients (p < 0.0001). Among oral cavity cancer patients, rural patients were 51% less likely to get diagnosed at young age compared with urban patients (95% CI: 0.27-0.89). Conclusions: Head and neck cancer screening is not routinely conducted so most show up at later stage of cancer. There is also evidence of disparities in age at HNC diagnosis based on rurality, race, and gender; targeted screening can help in reducing these disparities.

Geographic disparities in head and neck cancer survival in Upstate New York 2011–2019

“…However, our data did not feature any black patients residing in isolated small rural town focused or small rural town focused ZIP codes, which prevented evaluation for this effect. A study of HNC patients residing in Alabama by Mukherjee et al noted that patients residing in rural residence had more advanced stage cancer, as well as younger age at diagnosis 26 . However, we did not find a significant difference in distribution of these characteristics among our patients.…”

“…The net effects of these have been hypothesized to explain the overall higher mortality rates of rural communities compared to urban communities and has been termed the “rural mortality penalty.” 20 Other oncologic fields have documented rural residence as having impact on the care continuum similar to those stated for race and socioeconomic status on HNC patients, such as increased times to diagnosis for colorectal cancer, 21,22 as well as treatment receipt for prostate cancer 23 . However, the impact of rural residence on HNC outcomes are mixed in the literature 24–30 . Therefore, we sought to investigate this effect for the patients of our tertiary medical center, which resides in a large urban area surrounded by several rural areas.…”

The Impact of Smoking, Alcohol Use, Recurrent Disease, and Age on the Development of Neck Fibrosis in Head and Neck Cancer Patients Following Radiation Therapy

“…Although not robust independent risk factors, they may still aid in identifying an atrisk population. It has been shown in some studies that black patients are more likely than Caucasian patients to be diagnosed at a young age with HNC, in addition to rural patients being less likely to be diagnosed with HNC at a young age (19). Further research is needed to confirm the trends seen in this study across a larger population.…”

Effect of socioeconomic status on survival in patients with head and neck cancer

“…It is important to note that due to a lack of data regarding the cause of death, we were not able to calculate “disease‐specific survival,” which was done in other studies in the world but in significantly smaller cohorts 11 . In addition, we did not have data indicating the mode of treatment, the time elapsed from the moment of diagnosis to treatment, and the status of smoking, unlike databases that formed the basis for studies around the world 30–32 . The data were also missing regarding tumor staging, with 63.9% being classified as “unknown.” In addition, the data refer only to the status of residence at the time of diagnosis and do not reflect relocations from the center to the periphery or vice versa.…”

“…11 In addition, we did not have data indicating the mode of treatment, the time elapsed from the moment of diagnosis to treatment, and the status of smoking, unlike databases that formed the basis for studies around the world. [30][31][32] The data were also missing regarding tumor staging, with 63.9% being classified as "unknown." In addition, the data refer only to the status of residence at the time of diagnosis and do not reflect relocations from the center to the periphery or vice versa.…”