Dataset Information

Assessment of spatial variation in breast cancer-specific mortality using Louisiana SEER data.

ABSTRACT: BACKGROUND:Previous studies suggest spatial differences in mortality for many types of cancer, including breast cancer. Identifying explanations for these spatial differences results in a better understanding of what leads to longer survival time. METHODS:We used a Bayesian accelerated failure time model with spatial frailty terms to investigate potential spatial differences in breast cancer mortality following breast cancer diagnosis using 2000-2013 Louisiana SEER data. RESULTS:There are meaningful spatial differences in breast cancer mortality across the parishes of Louisiana, even after adjusting for known demographic and clinical risk factors. For example, the average survival time of a woman diagnosed in Orleans parish was 1.51 times longer than that of a woman diagnosed in Terrebonne parish. Additionally, there is evidence to suggest shorter survival times in lower income parishes along the Red and Mississippi Rivers, as well as parishes with lower socioeconomic status, less access to care and fresh food, worse quality of care, and more workers in certain industries. CONCLUSION:The addition of spatial frailties to account for an individual's geographic location is useful when analyzing breast cancer mortality data. Our findings suggest that survival following breast cancer diagnosis could potentially be improved if socioeconomic status differences were addressed, healthcare improved in quality and became more accessible, and certain industrial situations were improved for individuals diagnosed in parishes identified as having shorter average survival times.

SUBMITTER: Carroll R

PROVIDER: S-EPMC5659900 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Assessment of spatial variation in breast cancer-specific mortality using Louisiana SEER data.

Carroll Rachel R Lawson Andrew B AB Jackson Chandra L CL Zhao Shanshan S

Social science & medicine (1982) 20170928

<h4>Background</h4>Previous studies suggest spatial differences in mortality for many types of cancer, including breast cancer. Identifying explanations for these spatial differences results in a better understanding of what leads to longer survival time.<h4>Methods</h4>We used a Bayesian accelerated failure time model with spatial frailty terms to investigate potential spatial differences in breast cancer mortality following breast cancer diagnosis using 2000-2013 Louisiana SEER data.<h4>Result ...[more]

PMID: 28985516

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Project description:The presence of toxic metals in soil per se, and in soil impacted by mining, industry, agriculture and urbanisation in particular, is a major concern for both human health and ecotoxicology. The dual aim of this study was: to ascertain whether topsoil composition could influence the spatial distribution of mortality due to different types of cancer and to identify possible errors committed by epidemiological studies which analyse soil composition data as a closed number system. We conducted an ecological cancer mortality study, covering 861,440 cancer deaths (27 cancer sites) in 7917 Spanish mainland towns, from 1999 to 2008. Topsoil levels of Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn were determined by ICP-MS at 13,317 sampling points. We transformed the topsoil data in two ways, i.e. log transformation and centred logratio transformation. Principal factor analysis was performed to obtain independent latent factors for the transformed variables. To estimate the effect on mortality of topsoil factor loadings, we fitted Besag, York and Mollié models embedded in geostatistical-spatial models. This model included soil sample locations and town centroids (non-aligned data), fitted using the integrated nested Laplace approximation (INLA) as a tool for Bayesian inference and stochastic partial differential equations (SPDE). All results were adjusted for socio-demographic variables. The results indicated that soil composition could have an influence on the spatial distribution and mortality patterns of cancer. The analysis adjusted for socio-demographic variables showed excess male mortality due to digestive system tumours in areas with soils containing higher Cd, Pb, Zn, Mn and Cu concentrations, bladder cancer in areas with soils containing higher Cd concentrations, and brain cancer in areas with soils containing As. In both sexes, cancer of oesophagus was associated with soils containing a higher lead content, while lung cancer was associated with soils containing a higher copper content. Stress should be laid on the importance of taking into account the compositional nature of the data in this type of analysis.

Dataset Information

Assessment of spatial variation in breast cancer-specific mortality using Louisiana SEER data.

Publications

Assessment of spatial variation in breast cancer-specific mortality using Louisiana SEER data.

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