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Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location

An increasing number of studies have identified spatial differences in breast cancer survival. However little is known about whether the structure and dynamics of this spatial inequality are consistent across a region. This study aims to evaluate the spatially varying nature of predictors of spatial...

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Autores principales: Hsieh, Jeff Ching-Fu, Cramb, Susanna M., McGree, James M., Dunn, Nathan A. M., Baade, Peter D., Mengersen, Kerrie L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4857928/
https://www.ncbi.nlm.nih.gov/pubmed/27149274
http://dx.doi.org/10.1371/journal.pone.0155086
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author Hsieh, Jeff Ching-Fu
Cramb, Susanna M.
McGree, James M.
Dunn, Nathan A. M.
Baade, Peter D.
Mengersen, Kerrie L.
author_facet Hsieh, Jeff Ching-Fu
Cramb, Susanna M.
McGree, James M.
Dunn, Nathan A. M.
Baade, Peter D.
Mengersen, Kerrie L.
author_sort Hsieh, Jeff Ching-Fu
collection PubMed
description An increasing number of studies have identified spatial differences in breast cancer survival. However little is known about whether the structure and dynamics of this spatial inequality are consistent across a region. This study aims to evaluate the spatially varying nature of predictors of spatial inequality in relative survival for women diagnosed with breast cancer across Queensland, Australia. All Queensland women aged less than 90 years diagnosed with invasive breast cancer from 1997 to 2007 and followed up to the end of 2008 were extracted from linked Queensland Cancer Registry and BreastScreen Queensland data. Bayesian relative survival models were fitted using various model structures (a spatial regression model, a varying coefficient model and a finite mixture of regressions model) to evaluate the relative excess risk of breast cancer, with the use of Markov chain Monte Carlo computation. The spatially varying coefficient models revealed that some covariate effects may not be constant across the geographic regions of the study. The overall spatial patterns showed lower survival among women living in more remote areas, and higher survival among the urbanised south-east corner. Notwithstanding this, the spatial survival pattern for younger women contrasted with that for older women as well as single women. This complex spatial interplay may be indicative of different factors impacting on survival patterns for these women.
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spelling pubmed-48579282016-05-13 Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location Hsieh, Jeff Ching-Fu Cramb, Susanna M. McGree, James M. Dunn, Nathan A. M. Baade, Peter D. Mengersen, Kerrie L. PLoS One Research Article An increasing number of studies have identified spatial differences in breast cancer survival. However little is known about whether the structure and dynamics of this spatial inequality are consistent across a region. This study aims to evaluate the spatially varying nature of predictors of spatial inequality in relative survival for women diagnosed with breast cancer across Queensland, Australia. All Queensland women aged less than 90 years diagnosed with invasive breast cancer from 1997 to 2007 and followed up to the end of 2008 were extracted from linked Queensland Cancer Registry and BreastScreen Queensland data. Bayesian relative survival models were fitted using various model structures (a spatial regression model, a varying coefficient model and a finite mixture of regressions model) to evaluate the relative excess risk of breast cancer, with the use of Markov chain Monte Carlo computation. The spatially varying coefficient models revealed that some covariate effects may not be constant across the geographic regions of the study. The overall spatial patterns showed lower survival among women living in more remote areas, and higher survival among the urbanised south-east corner. Notwithstanding this, the spatial survival pattern for younger women contrasted with that for older women as well as single women. This complex spatial interplay may be indicative of different factors impacting on survival patterns for these women. Public Library of Science 2016-05-05 /pmc/articles/PMC4857928/ /pubmed/27149274 http://dx.doi.org/10.1371/journal.pone.0155086 Text en © 2016 Hsieh et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hsieh, Jeff Ching-Fu
Cramb, Susanna M.
McGree, James M.
Dunn, Nathan A. M.
Baade, Peter D.
Mengersen, Kerrie L.
Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location
title Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location
title_full Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location
title_fullStr Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location
title_full_unstemmed Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location
title_short Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location
title_sort spatially varying coefficient inequalities: evaluating how the impact of patient characteristics on breast cancer survival varies by location
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4857928/
https://www.ncbi.nlm.nih.gov/pubmed/27149274
http://dx.doi.org/10.1371/journal.pone.0155086
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