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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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 |
work_keys_str_mv |
AT mustafaandkhoie geographicdisparitiesinsaskatchewanprostatecancerincidenceanditsassociationwithphysiciandensityanalysisusingbayesianmodels AT michaelszafron geographicdisparitiesinsaskatchewanprostatecancerincidenceanditsassociationwithphysiciandensityanalysisusingbayesianmodels |
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