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Open Access 01-12-2021 | Prostate Cancer | Research article

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

Authors: Mustafa Andkhoie, Michael Szafron

Published in: BMC Cancer | Issue 1/2021

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.

Committee CCSA. Canadian Cancer Statistics 2019. Toronto; 2019 Sept 2019.

Table 13-10-0762-01 Number of new cases and age-standardized rates of primary cancer, by stage at diagnosis, selected cancer type and sex: Statistics Canada; 2020.

Andkhoie M, Szafron M. The impact of geographic location on Saskatchewan prostate Cancer patient treatment choices: a multilevel and spatial analysis. J Rural Health 2020 DOI: https://doi.org/10.1111/jrh.12471, 36, 4, 564, 576.

Andkhoie M, Szafron M. Geographic factors associated with time-to-treatment outcomes for radiation therapy among localized prostate cancer patients in Saskatchewan. J Cancer Policy. 2020;26:100259. https://doi.org/10.1016/j.jcpo.2020.100259.CrossRef

Moazzami B. Fewer & older: population and demographic crossroads in rural Saskatchewan. Canada: Strengthening Rural Canada; 2015.

Laing KA, Bramwell SP, McNeill A, Corr BD, Lam TB. Prostate cancer in Scotland: does geography matter? An analysis of incidence, disease characteristics and survival between urban and rural areas. J Clin Urol. 2014;7(3):176–84. https://doi.org/10.1177/2051415813512303.CrossRef

Carriere R, Adam R, Fielding S, Barlas R, Ong Y, Murchie P. Rural dwellers are less likely to survive cancer – an international review and meta-analysis. Health & lace. 2018;53:219–27. https://doi.org/10.1016/j.healthplace.2018.08.010.CrossRef

Unger JM, Moseley A, Symington B, Chavez-MacGregor M, Ramsey SD, Hershman DL. Geographic Distribution and Survival Outcomes for Rural Patients With Cancer Treated in Clinical Trials. JAMA Network Open. 2018;1(4):e181235-e DOI: https://doi.org/10.1001/jamanetworkopen.2018.1235.

Papa N, Lawrentschuk N, Muller D, MacInnis R, Ta A, Severi G, et al. Rural residency and prostate cancer specific mortality: results from the Victorian Radical Prostatectomy Register. Australian and New Zealand Journal of Public Health. 2014;38(5):449–54 DOI: https://doi.org/10.1111/1753-6405.12210.

10.

Afshar N, English DR, Milne RL. Rural-urban residence and cancer survival in high-income countries: a systematic review. Cancer. 2019;125(13):2172–84. https://doi.org/10.1002/cncr.32073.CrossRefPubMed

11.

Nair BV, Schuler R, Stewart S, Taylor-Gjevre RM. Self-reported barriers to healthcare access for rheumatoid arthritis patients in rural and northern Saskatchewan: a mixed methods study. Musculoskeletal Care. 2016;14(4):243–51. https://doi.org/10.1002/msc.1146.CrossRefPubMed

12.

Karunanayake CP, Rennie DC, Hagel L, Lawson J, Janzen B, Pickett W, et al. Access to specialist Care in Rural Saskatchewan: the Saskatchewan rural health study. Healthcare (Basel). 2015;3(1):84–99. https://doi.org/10.3390/healthcare3010084.CrossRef

13.

Physician in Canada, 2018. Ottawa: Canadian Institute for Health Information.; 2019.

14.

Macinko J, Starfield B, Shi L. Quantifying the health benefits of primary care physician supply in the United States. Int J Health Serv. 2007;37(1):111–26. https://doi.org/10.2190/3431-G6T7-37M8-P224.CrossRefPubMed

15.

Coughlin SS, Leadbetter S, Richards T, Sabatino SA. Contextual analysis of breast and cervical cancer screening and factors associated with health care access among United States women, 2002. Soc Sci Med. 2008;66(2):260–75. https://doi.org/10.1016/j.socscimed.2007.09.009.CrossRefPubMed

16.

Ferrante JM, Gonzalez EC, Pal N, Roetzheim RG. Effects of physician supply on early detection of breast cancer. J Am Board Fam Pract. 2000;13(6):408–14. https://doi.org/10.3122/15572625-13-6-408.CrossRefPubMed

17.

Fleisher JM, Lou JQ, Farrell M. Relationship between physician supply and breast cancer survival: a geographic approach. J Community Health. 2008;33(4):179–82. https://doi.org/10.1007/s10900-008-9090-z.CrossRefPubMed

18.

Gorey KM, Luginaah IN, Holowaty EJ, Fung KY, Hamm C. Associations of physician supplies with breast cancer stage at diagnosis and survival in Ontario, 1988 to 2006. Cancer. 2009;115(15):3563–70. https://doi.org/10.1002/cncr.24401.CrossRefPubMed

19.

Yao N, Foltz SM, Odisho AY, Wheeler DC. Geographic analysis of urologist density and prostate Cancer mortality in the United States. PLoS One. 2015;10(6):e0131578. https://doi.org/10.1371/journal.pone.0131578.CrossRefPubMedPubMedCentral

20.

Aneja S, Yu JB. The impact of county-level radiation oncologist density on prostate cancer mortality in the United States. Prostate Cancer Prostatic Dis. 2012;15(4):391–6. https://doi.org/10.1038/pcan.2012.28.CrossRefPubMed

21.

Nguyen KD, Hyder ZZ, Shaw MD, Maness SB, Cookson MS, Patel SG, et al. Effects of primary care physician density, urologist presence, and insurance status on stage of diagnosis for urologic malignancies. Cancer Epidemiol. 2018;52:10–4. https://doi.org/10.1016/j.canep.2017.10.012.CrossRefPubMed

22.

Ananthakrishnan AN, Hoffmann RG, Saeian K. Higher physician density is associated with lower incidence of late-stage colorectal cancer. J Gen Intern Med. 2010;25(11):1164–71. https://doi.org/10.1007/s11606-010-1457-z.CrossRefPubMedPubMedCentral

23.

Saskatchewan e. Covered Population 2015. Saskatchewan: eHealth Saskatchewan; 2015 June 30, 2015.

24.

Saskatchewan e. Saskatchewan Health Coverage Reports Saskatchewan: eHealth Saskatchewan; 2020 [Available from: https://opendata.ehealthsask.ca/MicroStrategyPublic/asp/Main.aspx.

25.

Crombie IK, Cramer N. Five-year age-specific incidence rates. I. Their nature and limitations. J Epidemiol Community Health. 1980;34(3):223–8. https://doi.org/10.1136/jech.34.3.223.CrossRefPubMedPubMedCentral

26.

Canadian Physician Data Canada: Canadian Medical Association; 2020 [Available from: https://www.cma.ca/canadian-physician-data.

27.

Lukka H, Warde P, Pickles T, Morton G, Brundage M, Souhami L, et al. Controversies in prostate cancer radiotherapy: consensus development. Can J Urol. 2001;8(4):1314–22.PubMed

28.

Ayubi E, Mansournia MA, Motlagh AG, Mosavi-Jarrahi A, Hosseini A, Yazdani K. Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic. Epidemiol Health. 2017;39:e2017021. https://doi.org/10.4178/epih.e2017021.CrossRefPubMedPubMedCentral

29.

Besag J, York J, Mollié A. Bayesian image restoration, with two applications in spatial statistics. Ann Inst Stat Math. 1991;43(1):1–20. https://doi.org/10.1007/BF00116466.CrossRef

30.

Anselin L. Global Spatial Autocorrelation. Github; 2018.

31.

Chaix B, Merlo J, Chauvin P. Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France. J Epidemiol Community Health. 2005;59(6):517–26. https://doi.org/10.1136/jech.2004.025478.CrossRefPubMedPubMedCentral

32.

Anselin LF, R. J. G. M.; Rey, S.J. Advances in Spatial Econometrics. Anselin LF, M. M.; Hewings, G. J. D.; Nijkamp, P.; Snickars, F., editor. New York: Springer; 2004, DOI: https://doi.org/10.1007/978-3-662-05617-2.

33.

Anselin L. Local Indicators of Spatial Association - LISA. Geographic Analysis. 1995;27(2):93–115 DOI: j.1538–4632.1995.tb00338.x.

34.

Kulldorff M. A spatial scan statistic. Communications in Statistics - Theory and Methods. 2007;26(6):1481–96. https://doi.org/10.1080/03610929708831995.CrossRef

35.

Han J, Zhu L, Kulldorff M, Hostovich S, Stinchcomb DG, Tatalovich Z, et al. Using Gini coefficient to determining optimal cluster reporting sizes for spatial scan statistics. Int J Health Geogr. 2016;15(1):27. https://doi.org/10.1186/s12942-016-0056-6.CrossRefPubMedPubMedCentral

36.

Dohoo I, Martin W, Stryhn H. Methods in epidemiologic research. Charlotte Town: VER Inc.; 2012.

37.

Goovaerts P, Gebreab S. How does Poisson kriging compare to the popular BYM model for mapping disease risks? Int J Health Geogr. 2008;7(1):6. https://doi.org/10.1186/1476-072X-7-6.CrossRefPubMedPubMedCentral

38.

Lawson AB, Browne WJ, Vidal Rodeiro CL. Disease Mapping with WinBUGS and MLwiN2003.

39.

Johnson GD. Small area mapping of prostate cancer incidence in New York state (USA) using fully Bayesian hierarchical modelling. Int J Health Geogr. 2004;3(1):29. https://doi.org/10.1186/1476-072X-3-29.CrossRefPubMedPubMedCentral

40.

Thomas A, Best N, Lunn D, Arnold R, Spiegelhalter D. GeoBUGS User Manual2014.

41.

Lawson AB. Bayesian disease mapping: hierarchical modeling in spatial epidemiology: Taylor & Francis group; 2009.

42.

Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences. Stat Sci. 1992;7(4):457–511.

43.

Brooks SP, Gelman A. General methods for monitoring convergence of iterative simulations. J Comput Graph Stat. 1998;7(4):434–55. https://doi.org/10.1080/10618600.1998.10474787.CrossRef

44.

Heidelberger P, Welch PD. Simulation run length control in the presence of an initial transient. Oper Res. 1983;31(6):1109–44. https://doi.org/10.1287/opre.31.6.1109.CrossRef

45.

Geweke JF. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. Federal Reserve Bank of Minneapolis; University of Minnesota; 1991.

46.

Raftery AE, Lewis SM. [practical Markov chain Monte Carlo]: comment: one long run with diagnostics: implementation strategies for Markov chain Monte Carlo. Stat Sci. 1992;7(4):493–7.

47.

Raftery AE, Lewis SM. The number of iterations, convergence diagnostics and generic Metropolis algorithms. Practical Markov chain Monte Carlo. London: Chapman and Hill; 1995.

48.

Anselin L, Syabri I, Kho Y. GeoDa: an introduction to spatial data analysis. Geographic Analysis. 2006;38(1):5–22. https://doi.org/10.1111/j.0016-7363.2005.00671.x.CrossRef

49.

Kulldorff M, Information Management Services I. SaTScanTM v9.4: Software for the spatial and space-time scan statistics. 2015.

50.

QGIS.org. QGIS Geographic Information System. Open Source Geospatial Foundation 2018.

51.

Lunn D, Spiegelhalter D, Thomas A, Best N. The BUGS project: Evolution, critique, and future directions. Stat Med. 2009;28(25):3049–67. https://doi.org/10.1002/sim.3680.CrossRefPubMed

52.

Plummer M, Best N, Cowles K, Vines K, Sarkar D, Bates D, et al. Package ‘coda’. CRAN; 2019.

53.

Catelan D, Lagazio C, Biggeri A. A hierarchical Bayesian approach to multiple testing in disease mapping. Biom J. 2010;52(6):784–97. https://doi.org/10.1002/bimj.200900209.CrossRefPubMedPubMedCentral

54.

Plascak JJ, Fisher JL, Paskett ED. Primary care physician supply, insurance type, and late-stage cancer diagnosis. Am J Prev Med. 2015;48(2):174–8. https://doi.org/10.1016/j.amepre.2014.08.014.CrossRefPubMed

55.

Ross LE, Hall IJ, Howard DL, Rim SH, Richardson LC. Primary care physicians beliefs about prostate-specific antigen evidence uncertainty, screening efficacy, and test use. J Natl Med Assoc. 2018;110(5):491–500. https://doi.org/10.1016/j.jnma.2017.12.007.CrossRefPubMed

56.

Nyame YA, Gulati R, Tsodikov A, Gore JL, Etzioni R. Prostate-Specific Antigen Screening and Recent Increases in Advanced Prostate Cancer. JNCI Cancer Spectr. 2021;5(1):pkaa098 DOI: https://doi.org/10.1093/jncics/pkaa098.

57.

Ilic D, Neuberger MM, Djulbegovic M, Dahm P. Screening for prostate cancer. Cochrane Database Syst Rev. 2013;1:CD004720. https://doi.org/10.1002/14651858.CD004720.pub3.CrossRef

58.

Shoag JE, Nyame YA, Gulati R, Etzioni R, Hu JC. Reconsidering the trade-offs of prostate Cancer screening. N Engl J Med. 2020;382(25):2465–8. https://doi.org/10.1056/NEJMsb2000250.CrossRefPubMedPubMedCentral

59.

Jemal A, Fedewa SA, Ma J, Siegel R, Lin CC, Brawley O, et al. Prostate Cancer incidence and PSA testing patterns in relation to USPSTF screening recommendations. JAMA. 2015;314(19):2054–61. https://doi.org/10.1001/jama.2015.14905.CrossRefPubMed

60.

Penchansky R, Thomas JW. The concept of access: definition and relationship to consumer satisfaction. Med Care. 1981;19(2):127–40. https://doi.org/10.1097/00005650-198102000-00001.CrossRefPubMed

61.

Wilson CR, Rourke J, Oandasan IF, Bosco C. Progress made on access to rural health care in Canada. Can Fam Physician. 2020;66(1):31–6.PubMedCentral

Title: Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models
Authors: Mustafa Andkhoie
Michael Szafron
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Prostate Cancer
Prostate Cancer
Published in: BMC Cancer / Issue 1/2021
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-021-08646-2

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