Abstract A30: Affordability of screening, race and marital status predict early detection of breast cancer: Analysis of cancer registry data
Authors: Chandak Aastha , Nayar Preethy , Kan Ge , Gupta Niodita 
Published: May 2019

Background: Breast cancer is the most common cancer diagnosis among women in Nebraska. Early diagnosis of breast cancer provides opportunities for better prognosis and treatment options and thereby improves chances of survival. Nebraska is predominantly a rural state, and hence, in addition to problems of affordability of health care due to lack of insurance or under-insurance, the people of rural Nebraska face unique challenges with regards to the availability and accessibility of cancer screening services. The purpose of this study was to examine whether access to cancer screening services, in terms of three dimensions: affordability, availability and accessibility, predict the stage of diagnosis for women diagnosed with breast cancer in Nebraska.

Methods: Data on breast cancer cases in Nebraska were obtained from the Nebraska Cancer Registry for the years 2008 to 2012. Proximity to the nearest screening center was calculated as the shortest distance between the population weighted centroid of each census tract in Nebraska and the nearest screening facility, using geocoded facility locations available from the United States Food and Drug Administration website. Spatial accessibility to primary care provider (PCP) was calculated using the two-step floating catchment area method using geocoded PCP locations, using data from the University of Nebraska Medical Center Health Professions Tracking Service annual survey database. Hierarchical logistic regression models adjusted for age, race, ethnicity, marital status, rurality of residence and county poverty level were examined to assess the association of type of insurance: Medicare, Medicaid, Other (including TRICARE, Military, Veterans Affairs Indian/Public Health Service) and Private, supply of screening centers, proximity to screening center and spatial accessibility to primary care physicians with the stage at diagnosis of breast cancer. Breast cancer stage at diagnosis was categorized as early (in-situ or localized stage) or late (regional or distant stage). Geocoding and proximity distance calculations were done using ArcGIS 10.3.2 and statistical analyses were conducted using STATA 14 software.

Results: Among 4,975 women aged 40 years or older and diagnosed with breast cancer in Nebraska between 2008 and 2012, 72.3% were diagnosed at an early stage (in-situ or localized). The results from the hierarchical logistic regression found that women who were uninsured were less likely (Odds Ratio [O.R]: 0.42; 95% Confidence Interval [C.I]: 0.25-0.73) to be diagnosed early and those women who had Medicaid coverage were also less likely (O.R: 0.56; 95% C.I: 0.40-0.78) to be diagnosed early, as compared to women having private insurance. Further, married women were 1.3 times more likely (O.R: 1.25; 95% C.I: 1.10-1.44) to be diagnosed early, and white women were 1.4 times more likely (O.R: 1.36; 95% C.I: 1.04-1.77) to be diagnosed early.

Conclusion: Affordability of cancer screening services plays an important role in early detection of breast cancer. Hence, the coverage of preventive services through the Affordable Care Act is likely to be a positive policy change leading to higher screening rates and thereby, higher rates of early detection of breast cancer. Further, there exist racial disparities in early diagnosis of breast cancer that may be due to differential access to screening services. Targeted policy efforts will be needed to address these disparities to improve outcomes of breast cancer for all race groups.

Citation Format: Aastha Chandak, Preethy Nayar, Ge Kan, Niodita Gupta. Affordability of screening, race and marital status predict early detection of breast cancer: Analysis of cancer registry data. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr A30.