Cancer incidence, stage at diagnosis and outcomes among Manitoba First Nations people living on and off reserve: a retrospective population-based analysis
Bibliographic record
Abstract
<h3>Background:</h3> Substantial cancer-related disparities exist between First Nations and non-Indigenous Canadians. The objectives of this study were to compare cancer incidence, stage at diagnosis and mortality outcomes between Status First Nations people living on reserve and off reserve in Manitoba. <h3>Methods:</h3> We conducted a retrospective analysis of population-level administrative health databases in Manitoba. Cancers diagnosed between Apr. 1, 2004, and Mar. 31, 2011, were linked with the Indian Registry System and 5 provincial databases. We compared differences in baseline characteristics, cancer incidence, site and stage at diagnosis between Status First Nations patients living on and off reserve. Linear regression models examined trends in annual cancer incidence. Cox proportional hazard regression models examined mortality. <h3>Results:</h3> There were 1524 newly diagnosed cancers among Status First Nations people in Manitoba between Apr. 1, 2004, and Mar. 31, 2011. First Nations people living on reserve were significantly older than those living off reserve (<i>p</i> < 0.001) and had higher Charlson Comorbidity Index scores at diagnosis (<i>p</i> = 0.01). A lower proportion of on-reserve patients than off-reserve patients were diagnosed with stage I cancers (21.7% v. 26.9%, <i>p</i> = 0.02). There were no differences in annual cancer incidence between groups. The adjusted incidence of cancer over the combined study years was higher in the off-reserve group than in the on-reserve group (287.9 v. 247.9 per 100 000, <i>p</i> = 0.02). No significant differences in mortality were found. <h3>Interpretation:</h3> The lower proportion of on-reserve patients diagnosed with cancer at stage I is concerning, as it suggests less access to screening services or delays in diagnosis. Further research is needed to understand patterns in diagnosis and differences in cancer site and overall cancer incidence between First Nations people living on and off reserve.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".