The Impact of Geographic Location on Saskatchewan Prostate Cancer Patient Treatment Choices: A Multilevel and Spatial Analysis
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to estimate the relationship between remoteness and the initial chosen treatment (active surveillance/watchful waiting (AS/WW), radiation therapy (RT), surgery, chemotherapy (CT), or hormonal therapy (HT) for prostate cancer (PCa). METHODS: This study built 2 multilevel generalized linear models via a binomial link for each treatment type (one with only covariates and one with 2 additional study variables to the covariate model). The study also used cluster analysis using the Global and local Moran's I spatial statistics to find any complementary results to the above models. RESULTS: This study found that patients living in the rural areas have lower odds (OR = 0.59; 95% CI, 0.45-0.77; P < .001) of having surgery compared to patients living in the greater urban areas. Among patients whose closest PCa assessment center is Regina, patients living in the greater urban areas have higher odds (OR = 1.66; 95% CI, 1.03-2.68; P = .039) of choosing RT compared to patients living in the rural areas. There was no statistically significant effect of remoteness on whether one chose HT or AS/WW. CONCLUSIONS: There are regional disparities to PCa treatment utilization. Living in rural areas affects choosing surgery and, in certain localized geographical regions, affects choosing RT. For non-curative treatments (ie, AS/WW and HT), we did not find any association with geographical remoteness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".