Predictors of prostate cancer outcomes in Saskatchewan
| dc.contributor.advisor | Szafron, Michael | |
| dc.contributor.committeeMember | D'Arcy, Carl | |
| dc.contributor.committeeMember | Farag, Marwa | |
| dc.contributor.committeeMember | Feng, Cindy | |
| dc.contributor.committeeMember | Osgood, Nathaniel | |
| dc.contributor.committeeMember | Tonita, Jon | |
| dc.creator | Andkhoie, Mustafa | |
| dc.creator.orcid | 0000-0002-6600-0797 | |
| dc.date.accessioned | 2021-12-03T16:42:45Z | |
| dc.date.available | 2021-12-03T16:42:45Z | |
| dc.date.created | 2022-06 | |
| dc.date.issued | 2021-12-03 | |
| dc.date.submitted | June 2022 | |
| dc.date.updated | 2021-12-03T16:42:45Z | |
| dc.description.abstract | Background: Prostate cancer (PCa) is one of the leading causes of cancer mortality and incidence in Canada. Saskatchewan has one of highest mortality and incidence rates in Canada, and this doctoral research explores possible reasons for the higher mortality and incidence rates in Saskatchewan compared to the other provinces. While reasons for these PCa outcomes are not known, we hypothesize healthcare access factors may influence PCa outcomes, including PCa incidence, treatment usage and time trends in Saskatchewan, and we hypothesize additional factors may affect PCa treatment decision-making. To explore these hypotheses, in this dissertation we study the following research questions: (1) “Is the PCa incidence in Saskatchewan affected by changes in family physician density, the remoteness level of where a patient lives, and the closest PCa assessment centre from where a patient lives?”; (2) “Are the PCa treatment utilization rates in Saskatchewan affected by changes in the remoteness level of where a patient lives and the closest PCa assessment centre from where a patient lives?”; (3) “Are the PCa time-to-treatment outcomes in Saskatchewan affected by changes in the remoteness level of where a patient lives and the closest PCa assessment centre from where a patient lives?”; and (4) “What factors and corresponding themes in the literature have been identified to affect the treatment decision-making of localized prostate cancer patients in Canada and the United States?”. Methods: To explore research questions one, two, and three, we used data from: (1) Saskatchewan Cancer Registry, (2) Statistics Canada’s Index of Remoteness, (3) Canadian Medical Association, and (4) Saskatchewan Covered Population. To explore research question four, we used data from: (1) MEDLINE, (2) EMBASE, (3) CINAHL, (4) AMED and (5) PsycInfo. For our first research question, we estimated the standardized incidence ratios (SIRs) of PCa and their associations with family physician density, remoteness level of where a patient lives and closest PCa assessment centre from where a patient lives in Saskatchewan using the Besag, York and Mollie (BYM) Bayesian method. For our second research question, we built multilevel generalized linear models to estimate the relationship between treatment choice and factors including remoteness level of where a patient lives and closest PCa assessment centre from where a patient lives. For our third research question, we conducted multivariable analysis to assess whether remoteness level of where a patient lives and closest PCa assessment centre from where a patient lives are associated with PCa time-to-treatment outcomes. For our fourth research question, we conducted a scoping review using the process of Arksey and O’Malley to identify key factors commonly studied in localized PCa treatment decision-making. Results: Family physician density was negatively associated with SIRs of metastatic PCa (IRR = 0.935; 95% CrI: 0.880 to 0.998]) and SIR of high-risk PCa (IRR = 0.927 ; 95% CrI: 0.880 to 0.975). We found that patients living in the rural areas have lower odds (OR = 0.59; 95% CI: 0.45 to 0.77; P < .001) of having surgery compared to patients living in the greater urban areas. RT diagnosis-to-treatment time was positively correlated with the remoteness-index (IRR = 1.45; 95% CI: 1.21 to 1.75; P < .001). Five themes in localized PCa treatment decision-making were identified: treatment type, socioeconomic characteristics, personal reasons, psychological experience, and involvement in the decision-making process. Conclusions: Healthcare access factors were associated with PCa incidence, treatment choice and treatment delays in Saskatchewan. We found family physician density was negatively associated with incidence of high risk and metastatic PCa. There were regional disparities in PCa treatment choice and residents living in rural/remote areas were associated with delays for PCa treatment. We found five key factors associated with PCa treatment decision-making. This work informs future research and cancer care practices and policies to improve PCa patient outcomes in Saskatchewan and Canada. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/10388/13699 | |
| dc.subject | epidemiology | |
| dc.subject | prostate cancer | |
| dc.subject | prostatic neoplasm | |
| dc.subject | Bayesian statistics | |
| dc.subject | spatial analysis | |
| dc.subject | time to treatment | |
| dc.subject | treatment utilization | |
| dc.subject | treatment decision | |
| dc.subject | public health | |
| dc.subject | Saskatchewan | |
| dc.subject | Canada | |
| dc.title | Predictors of prostate cancer outcomes in Saskatchewan | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | School of Public Health | |
| thesis.degree.discipline | Epidemiology | |
| thesis.degree.grantor | University of Saskatchewan | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy (Ph.D.) |
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