A Geospatial Model to Identify Areas Associated with Late- Stage Breast Cancer: A Spatial Epidemiology Approach

Abstract

Objective: The aim of this study was to show how a geospatial model can be used to identify areas with a higher probability for late-stage breast cancer (BC) diagnoses. Methods: Our study considered an ecological design. Clinical records at a tertiary care hospital were reviewed in order to obtain the place of residence and stage of the disease, which was classified as early (0-IIA) and late (IIB-IV) and whose diagnoses were made during the 2013-2017 period. Then, they were geolocated to identify the distribution and spatial trend. Subsequently, the pattern of location, i.e. scattered, random and concentrated, was statistically assessed and a geospatial model was elaborated to determine the probability of late diagnoses in the state of Jalisco, Mexico. Result: There were 1 954 (N) geolocated BC diagnoses: 58.3% were late. During the five-year period, a southwest-northeast trend was identified, nearly 9.5% of the surface of Jalisco, where 6 out of 10 (n= 751) late- stage diagnoses were concentrated. A concentrated and statistically significant pattern was identified in the southern, central and northern Pacific area of Jalisco, where the geospatial model delimited the places with the highest probability of late clinical stages (p <0.05). Conclusion: The geographical differences associated with the late diagnoses of BC suggest it is necessary to adapt and focus the strategies for early detection as an alternative to create a major impact on the population. Reproducible analysis tools were used in other contexts where geolocation data are available to complement public policies and strategies aimed to control BC.

Exploring the geospatial epidemiology of breast cancer in Iran: identifying significant risk factors and spatial patterns for evidence-based prevention strategies

“…Urban Israeli women had higher mortality than rural women, highlighting potential environmental factors and complex interactions [ 53 ]. Mexico analysis identified clustering of late-stage diagnoses in southern, central, and northern coastal regions beyond the main metro area [ 54 ]. In Spain, higher mortality in western provinces was possibly related to screening, reproductive factors, and age [ 55 ].…”

Demographical and Epidemiological Contribution to Cancer Incidence in Delhi and Its Trends from 1991-2015

“…The variation in the trend of cancer due to demographical and epidemiological contribution has not been studied much both globally and in India [ 3 ]. Although the studies are conducted to assess the geospatial models to find the regional variations within a city or country [ 4 , 5 ]. Our extensive search of Indian literature found, one study that assessed the future burden of tobacco-related cancer in Delhi and another study, exploring the trend and prediction of cervical cancer incidence evaluating the impact of demographic and epidemiological changes [ 6 , 7 ].…”