The Association of Rural-Urban Inhabitation With Gastric Adenocarcinoma Mortality and Treatment: A Surveillance, Epidemiology, and End Results (SEER)-Based Study

Abstract

BackgroundGastric cancer is one of the most prevalent cancers in the world and the third most common cause of death from cancer. The diagnosis and treatment are often complex and require a multifaceted approach. Hence, appropriate and timely management is essential for better patient outcomes. Our aim was to determine if rural inhabitation affects the mortality of patients with gastric adenocarcinoma. If such an association exists, we propose to ascertain whether this is related to delayed diagnosis, differing tumor characteristics, or treatment inequalities. MethodsThe Cox model was applied to gastric adenocarcinoma cases diagnosed during 2004-2011 in American residents aged 20+ years in the Surveillance, Epidemiology, and End Results (SEER) program to determine the impact of rurality on mortality. Binary logistic regression was used to compare the odds of not receiving surgical treatment for localized tumors between rural and urban areas. It was also used to measure the association of rurality with stage at diagnosis (non-metastatic vs. metastatic). ResultsThere was a significant association of rurality on 5-year mortality [HR 1.14 (1.09-1.20), p < 0.01]. No significant association was observed between rural-urban residency and stage at diagnosis, with an odds ratio (OR) of 0.95 (0.87-1.03), p = 0.21. The median time from diagnosis to any first-course treatment was one month for both rural and urban counties. Rural residents were far more likely not to receive surgical treatment for localized tumors than their urban counterparts [OR 1.70 (1.41-2.05), p < 0.01]. A greater percentage of rural inhabitants had cardia tumors as compared to urban ones, 39.8% vs. 33.8% respectively. Non-cardia tumors were far less likely not to receive surgical treatment (i.e., more likely to receive surgical treatment) than cardia tumors , p < 0.01]. ConclusionsRurality is associated with worse gastric adenocarcinoma mortality. This may be due to a lesser probability of receiving surgical treatment for early-stage disease and differences in the primary site of the tumor between rural and urban counties, but not due to differences in stage at presentation. Future research should focus on improving health care access in rural communities.

Variation in Treatment Patterns of Patients with Early-Onset Gastric Cancer

“…We found patients with EOGC and LOGC residing in locations that were not adjacent to metropolitan areas were less likely to receive surgery than those residing in metropolitan areas ( Table 2 and Table S2 ). In analyses of SEER and California Cancer Registry data, patients of all ages with gastric cancer residing in rural areas were also less likely to receive surgery compared to those in urban areas, which was attributed to lower levels of educational attainment, lower median household income, longer commute times, less contact with oncology providers, and less access to health insurance [ 42 , 43 ].…”

Prediction models for the survival in patients with intestinal-type gastric adenocarcinoma: a retrospective cohort study based on the SEER database

“…SEER, as a data-accessible and publicly free database, collected data on the epidemiology of various malignancies. 11 The database contains patients’ demographics, primary tumour data, regional nodal data, vital status and survival. 12 …”

“…All data of patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) Regs 18 Custom Data (with Calculated Months Fields) between 2004 and 2015 in this retrospective cohort study. SEER, as a data-accessible and publicly free database, collected data on the epidemiology of various malignancies 11. The database contains patients’ demographics, primary tumour data, regional nodal data, vital status and survival 12…”

The impact of digital inequities on gastrointestinal cancer disparities in the United States

“…6 Social determinants of health (SDoH) such as socioeconomic status, race/ethnicity, and rurality contribute to inequitable access to care and mortality among patients with GIC. [7][8][9][10][11][12][13][14] In fact, prior studies have demonstrated that various SDoH comprises 80%-90% of modifiable contributors to population health outcomes among patients with cancer and other diseases. 15 Recently, the American Medical Informatics Association stated that the digital divide is an important underrecognized SDoH.…”

“…Despite the implementation of numerous policy measures to combat disparities, 2–5 GIC mortality is expected to increase substantially over the coming decades 6 . Social determinants of health (SDoH) such as socioeconomic status, race/ethnicity, and rurality contribute to inequitable access to care and mortality among patients with GIC 7–14 . In fact, prior studies have demonstrated that various SDoH comprises 80%–90% of modifiable contributors to population health outcomes among patients with cancer and other diseases 15 .…”