Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models

Abstract Background Saskatchewan has one of the highest incidence of prostate cancer (PCa) in Canada. This study assesses if geographic factors in Saskatchewan, including location of where patients live and physician density are affecting the PCa incidence. First, the objective of this study is to e...

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Main Authors: Mustafa Andkhoie, Michael Szafron
Format: Article
Language:English
Published: BMC 2021-08-01
Series:BMC Cancer
Subjects:
Online Access:https://doi.org/10.1186/s12885-021-08646-2
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spelling doaj-6910131a314d463d92e8d8b1d3e7fec22021-08-29T11:32:27ZengBMCBMC Cancer1471-24072021-08-0121111310.1186/s12885-021-08646-2Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian modelsMustafa Andkhoie0Michael Szafron1University of SaskatchewanUniversity of SaskatchewanAbstract Background Saskatchewan has one of the highest incidence of prostate cancer (PCa) in Canada. This study assesses if geographic factors in Saskatchewan, including location of where patients live and physician density are affecting the PCa incidence. First, the objective of this study is to estimate the PCa standardized incidence ratio (SIRs) in Saskatchewan stratified by PCa risk-level. Second, this study identifies clusters of higher than and lower than expected PCa SIRs in Saskatchewan. Lastly, this study identifies the association (if any) between family physician density and estimated PCa SIRs in Saskatchewan. Methods First, using Global Moran’s I, Local Moran’s I, and the Kuldorff’s Spatial Scan Statistic, the study identifies clusters of PCa stratified by risk-levels. Then this study estimates the SIRs of PCa and its association with family physician density in Saskatchewan using the Besag, York, and Mollie (BYM) Bayesian method. Results Higher than expected clusters of crude estimated SIR for metastatic PCa were identified in north-east Saskatchewan and lower than expected clusters were identified in south-east Saskatchewan. Areas in north-west Saskatchewan have lower than expected crude estimated SIRs for both intermediate-risk and low-risk PCa. Family physician density was negatively associated with SIRs of metastatic PCa (IRR: 0.935 [CrI: 0.880 to 0.998]) and SIRs of high-risk PCa (IRR: 0.927 [CrI: 0.880 to 0.975]). Conclusions This study identifies the geographical disparities in risk-stratified PCa incidence in Saskatchewan. The study identifies areas with a lower family physician density have a higher-than-expected incidences of metastatic and high-risk PCa. Hence policies to increase the number of physicians should ensure an equitable geographic distribution of primary care physicians to support early detection of diseases, including PCa.https://doi.org/10.1186/s12885-021-08646-2Prostate cancerProstatic neoplasmsGeographyEpidemiologySpatial analysisPhysician supply
collection DOAJ
language English
format Article
sources DOAJ
author Mustafa Andkhoie
Michael Szafron
spellingShingle Mustafa Andkhoie
Michael Szafron
Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models
BMC Cancer
Prostate cancer
Prostatic neoplasms
Geography
Epidemiology
Spatial analysis
Physician supply
author_facet Mustafa Andkhoie
Michael Szafron
author_sort Mustafa Andkhoie
title Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models
title_short Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models
title_full Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models
title_fullStr Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models
title_full_unstemmed Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models
title_sort geographic disparities in saskatchewan prostate cancer incidence and its association with physician density: analysis using bayesian models
publisher BMC
series BMC Cancer
issn 1471-2407
publishDate 2021-08-01
description Abstract Background Saskatchewan has one of the highest incidence of prostate cancer (PCa) in Canada. This study assesses if geographic factors in Saskatchewan, including location of where patients live and physician density are affecting the PCa incidence. First, the objective of this study is to estimate the PCa standardized incidence ratio (SIRs) in Saskatchewan stratified by PCa risk-level. Second, this study identifies clusters of higher than and lower than expected PCa SIRs in Saskatchewan. Lastly, this study identifies the association (if any) between family physician density and estimated PCa SIRs in Saskatchewan. Methods First, using Global Moran’s I, Local Moran’s I, and the Kuldorff’s Spatial Scan Statistic, the study identifies clusters of PCa stratified by risk-levels. Then this study estimates the SIRs of PCa and its association with family physician density in Saskatchewan using the Besag, York, and Mollie (BYM) Bayesian method. Results Higher than expected clusters of crude estimated SIR for metastatic PCa were identified in north-east Saskatchewan and lower than expected clusters were identified in south-east Saskatchewan. Areas in north-west Saskatchewan have lower than expected crude estimated SIRs for both intermediate-risk and low-risk PCa. Family physician density was negatively associated with SIRs of metastatic PCa (IRR: 0.935 [CrI: 0.880 to 0.998]) and SIRs of high-risk PCa (IRR: 0.927 [CrI: 0.880 to 0.975]). Conclusions This study identifies the geographical disparities in risk-stratified PCa incidence in Saskatchewan. The study identifies areas with a lower family physician density have a higher-than-expected incidences of metastatic and high-risk PCa. Hence policies to increase the number of physicians should ensure an equitable geographic distribution of primary care physicians to support early detection of diseases, including PCa.
topic Prostate cancer
Prostatic neoplasms
Geography
Epidemiology
Spatial analysis
Physician supply
url https://doi.org/10.1186/s12885-021-08646-2
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