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Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia

BACKGROUND: Treatment decisions for men diagnosed with prostate cancer depend on a range of clinical and patient characteristics such as disease stage, age, general health, risk of side effects and access. Associations between treatment patterns and area-level factors such as remoteness and socioeco...

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Autores principales: Cameron, Jessica K., Chandrasiri, Upeksha, Millar, Jeremy, Aitken, Joanne F., Cramb, Susanna, Dunn, Jeff, Frydenberg, Mark, Rashid, Prem, Mengersen, Kerrie, Chambers, Suzanne K., Baade, Peter D., Smith, David P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10642787/
https://www.ncbi.nlm.nih.gov/pubmed/37956143
http://dx.doi.org/10.1371/journal.pone.0293954
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author Cameron, Jessica K.
Chandrasiri, Upeksha
Millar, Jeremy
Aitken, Joanne F.
Cramb, Susanna
Dunn, Jeff
Frydenberg, Mark
Rashid, Prem
Mengersen, Kerrie
Chambers, Suzanne K.
Baade, Peter D.
Smith, David P.
author_facet Cameron, Jessica K.
Chandrasiri, Upeksha
Millar, Jeremy
Aitken, Joanne F.
Cramb, Susanna
Dunn, Jeff
Frydenberg, Mark
Rashid, Prem
Mengersen, Kerrie
Chambers, Suzanne K.
Baade, Peter D.
Smith, David P.
author_sort Cameron, Jessica K.
collection PubMed
description BACKGROUND: Treatment decisions for men diagnosed with prostate cancer depend on a range of clinical and patient characteristics such as disease stage, age, general health, risk of side effects and access. Associations between treatment patterns and area-level factors such as remoteness and socioeconomic disadvantage have been observed in many countries. OBJECTIVE: To model spatial differences in interventional treatment rates for prostate cancer at high spatial resolution to inform policy and decision-making. METHODS: Hospital separations data for interventional treatments for prostate cancer (radical prostatectomy, low dose rate and high dose rate brachytherapy) for men aged 40 years and over were modelled using spatial models, generalised linear mixed models, maximised excess events tests and k-means statistical clustering. RESULTS: Geographic differences in population rates of interventional treatments were found (p<0.001). Separation rates for radical prostatectomy were lower in remote areas (12.2 per 10 000 person-years compared with 15.0–15.9 in regional and major city areas). Rates for all treatments decreased with increasing socioeconomic disadvantage (radical prostatectomy 19.1 /10 000 person-years in the most advantaged areas compared with 12.9 in the most disadvantaged areas). Three groups of similar areas were identified: those with higher rates of radical prostatectomy, those with higher rates of low dose brachytherapy, and those with low interventional treatment rates but higher rates of excess deaths. The most disadvantaged areas and remote areas tended to be in the latter group. CONCLUSIONS: The geographic differences in treatment rates may partly reflect differences in patients’ physical and financial access to treatments. Treatment rates also depend on diagnosis rates and thus reflect variation in investigation rates for prostate cancer and presentation of disease. Spatial variation in interventional treatments may aid identification of areas of under-treatment or over-treatment.
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spelling pubmed-106427872023-11-14 Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia Cameron, Jessica K. Chandrasiri, Upeksha Millar, Jeremy Aitken, Joanne F. Cramb, Susanna Dunn, Jeff Frydenberg, Mark Rashid, Prem Mengersen, Kerrie Chambers, Suzanne K. Baade, Peter D. Smith, David P. PLoS One Research Article BACKGROUND: Treatment decisions for men diagnosed with prostate cancer depend on a range of clinical and patient characteristics such as disease stage, age, general health, risk of side effects and access. Associations between treatment patterns and area-level factors such as remoteness and socioeconomic disadvantage have been observed in many countries. OBJECTIVE: To model spatial differences in interventional treatment rates for prostate cancer at high spatial resolution to inform policy and decision-making. METHODS: Hospital separations data for interventional treatments for prostate cancer (radical prostatectomy, low dose rate and high dose rate brachytherapy) for men aged 40 years and over were modelled using spatial models, generalised linear mixed models, maximised excess events tests and k-means statistical clustering. RESULTS: Geographic differences in population rates of interventional treatments were found (p<0.001). Separation rates for radical prostatectomy were lower in remote areas (12.2 per 10 000 person-years compared with 15.0–15.9 in regional and major city areas). Rates for all treatments decreased with increasing socioeconomic disadvantage (radical prostatectomy 19.1 /10 000 person-years in the most advantaged areas compared with 12.9 in the most disadvantaged areas). Three groups of similar areas were identified: those with higher rates of radical prostatectomy, those with higher rates of low dose brachytherapy, and those with low interventional treatment rates but higher rates of excess deaths. The most disadvantaged areas and remote areas tended to be in the latter group. CONCLUSIONS: The geographic differences in treatment rates may partly reflect differences in patients’ physical and financial access to treatments. Treatment rates also depend on diagnosis rates and thus reflect variation in investigation rates for prostate cancer and presentation of disease. Spatial variation in interventional treatments may aid identification of areas of under-treatment or over-treatment. Public Library of Science 2023-11-13 /pmc/articles/PMC10642787/ /pubmed/37956143 http://dx.doi.org/10.1371/journal.pone.0293954 Text en © 2023 Cameron et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Cameron, Jessica K.
Chandrasiri, Upeksha
Millar, Jeremy
Aitken, Joanne F.
Cramb, Susanna
Dunn, Jeff
Frydenberg, Mark
Rashid, Prem
Mengersen, Kerrie
Chambers, Suzanne K.
Baade, Peter D.
Smith, David P.
Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia
title Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia
title_full Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia
title_fullStr Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia
title_full_unstemmed Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia
title_short Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia
title_sort disease mapping: geographic differences in population rates of interventional treatment for prostate cancer in australia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10642787/
https://www.ncbi.nlm.nih.gov/pubmed/37956143
http://dx.doi.org/10.1371/journal.pone.0293954
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