Renal Cell Carcinoma in the Canadian Indigenous Population
Bibliographic record
Abstract
Background: Diagnosis and treatment of renal cell carcinoma (RCC) might be different in Indigenous Canadians than in non-Indigenous Canadians. In this cohort study, we compared RCC presentation and treatments in Indigenous and non-Indigenous Canadians. Methods: Patients registered in the Canadian Kidney Cancer Information System treated at 16 institutions between 2011 and 2018 were included. Baseline patient, tumour, and treatment characteristics were compared between Indigenous and non-Indigenous Canadians. The primary objective was to determine if differences in RCC stage at diagnosis were evident between the groups. The secondary objective was to determine if treatments and outcomes were different between the groups. Results: During the study period, 105 of the 4529 registered patients self-identified as Indigenous. Those patients were significantly younger at the time of clinical diagnosis (57.9 ± 11.3 years vs. 62.0 ± 12.1 years, p = 0.0006) and had a family history prevalence of RCC that was double the prevalence in the non-Indigenous patients (14% vs. 7%, p = 0.004). Clinical stage at diagnosis was similar in the two groups (p = 0.61). The disease was metastatic at presentation in 11 Indigenous Canadians (10%) and in 355 non-Indigenous Canadians (8%). Comorbid conditions that could affect the management of RCC—such as obesity, renal disease, diabetes mellitus, and smoking—were more common in Indigenous Canadians (p < 0.05). Indigenous Canadians experienced a lower rate of active surveillance (p = 0.01). Treatments and median time to treatments were similar in the two groups. Conclusions: Compared with their non-Indigenous counterparts, Indigenous Canadian patients with RCC are diagnosed at an earlier age and at a similar clinical stage. Despite higher baseline comorbid conditions, clinical outcomes are not worse for Indigenous Canadians than for non-Indigenous Canadians.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".