Bibliographic record
Abstract
Introduction: Indigenous Peoples have higher morbidity rates and lower life expectancies than non-Indigenous Canadians.We aimed to identify disparities between Indigenous and non-Indigenous men regarding prostate cancer (PCa) screening, diagnoses, management, and outcomes.Methods: We studied an observational cohort of men diagnosed with PCa between June 2014 and October 2022.Men were prospectively enrolled in the province-wide Alberta Prostate Cancer Research Initiative.The primary outcomes were tumor characteristics (stage, grade, PSA) at diagnosis.Secondary outcomes were PSA testing rates, time from diagnosis to treatment, treatment modality, metastasis-free, cancer-specific, and overall survivals. Results:We examined 1 444 974 men for whom aggregate PSA testing data were available.Men in Indigenous communities were less likely to have PSA testing performed than men outside of Indigenous communities (32 vs. 46 PSA tests per 100 men [aged 50-70] within one year, p<0.001).Among 6049 men diagnosed with PCa, Indigenous men had higher-risk disease characteristics: a higher proportion of Indigenous men had PSA 10 ng/ml (48% vs. 30%, p<0.01),TNM stage T2 (75% vs. 47%, p<0.01), and Gleason grade group ≥2 (79% vs. 64%, p<0.01) compared to non-Indigenous men.With a median followup of 40 (IQR 25-65) months, Indigenous men were at higher risk of developing PCa metastases (HR 2.2, 95% CI 1.2-3.9,p=0.01) than non-Indigenous men.Conclusions: Despite receiving care in a universal healthcare system, Indigenous men were less likely to receive PSA testing and more likely to be diagnosed with aggressive tumors and develop prostate cancer metastases than non-Indigenous men.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.636 | 0.310 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".