Abstract

BackgroundLate stage of cancer at diagnosis is an important predictor of cancer mortality. In many areas worldwide, cancer registry systems, available data and mapping technologies can provide information about late stage cancer by geographical regions, offering valuable opportunities to identify areas where further investigation and interventions are needed. The current study examined geographical variation in late stage breast cancer incidence across eight states in the United States with the objective to identify areas that might benefit from targeted interventions.MethodsData from the Surveillance Epidemiology and End Results Program on late stage breast cancer incidence was used as dependent variable in regression analysis and certain factors known to contribute to high rates of late stage cancer (socioeconomic characteristics, health insurance characteristics, and the availability and utilization of cancer screening) as covariates. Geographic information systems were used to map and highlight areas that have any combination of high late stage breast cancer incidence and significantly associated risk factors.ResultsThe differences in mean rates of late stage breast cancer between eight states considered in this analysis are statistically significant. Factors that have statistically negative association with late stage breast cancer incidence across the eight states include: density of mammography facilities, percent population with Bachelor’s degree and English literacy while percent black population has statistically significant positive association with late stage breast cancer incidence.ConclusionsThis study describes geographic disparities in late stage breast cancer incidence and identifies areas that might benefit from targeted interventions. The results suggest that in the eight US states examined, higher rates of late stage breast cancer are more common in areas with predominantly black population, where English literacy, percentage of population with college degree and screening availability are low. The approach described in this work may be utilized both within and outside US, wherever cancer registry systems and technologies offer the same opportunity to identify places where further investigation and interventions for reducing cancer burden are needed.

Highlights

  • Late stage of cancer at diagnosis is an important predictor of cancer mortality

  • The objective of present study is to demonstrate the use of available data and geographic information systems to (1) examine geographic disparities in late stage breast cancer incidence, Tatalovich et al Int J Health Geogr (2015) 14:31 (2) identify factors that are associated with higher rates of late stage breast cancer across different geographic areas, and (3) highlight areas that might benefit from targeted interventions

  • To test for significant differences in late stage breast cancer incidence among the eight states, we run an analysis of variance and get an F statistic value of 4.241, with p < 0.0001, which indicates that the variation in mean rates of Late stage breast cancer (LSBC) by state is statistically significant

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Summary

Introduction

Cancer registry systems, available data and mapping technologies can provide information about late stage cancer by geographical regions, offering valuable opportunities to identify areas where further investigation and interventions are needed. The current study examined geographical variation in late stage breast cancer incidence across eight states in the United States with the objective to identify areas that might benefit from targeted interventions. Breast cancer is the top cancer in women worldwide and is increasing in developing countries where the majority of cases are diagnosed in late stages [1]. (2) identify factors that are associated with higher rates of late stage breast cancer across different geographic areas, and (3) highlight areas that might benefit from targeted interventions. Late stage breast cancer (LSBC): theoretical foundation Many factors contribute to LSBC at diagnosis. Among the major factors are the underlying biological aggressiveness of the disease [2]; demographic and socio-economic characteristics [3,4,5,6], health insurance status [7, 8], accessibility to healthcare and diagnostic services [9,10,11], the availability and utilization screening tests [12]

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