Stage, treatment and outcomes for patients with breast cancer in British Columbia in 2002: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: There are very few long-term Canadian data on breast cancer outcomes by stage. We described the stage, treatment and outcomes of breast cancer at a population level for patients in British Columbia. METHODS: This population-based cohort study included almost all patients with incident breast cancer registered in 2002 (about 97.6% registry case completeness). For these patients, information on stage, primary local surgery, radiotherapy, chemotherapy, hormone therapy and survival outcome (based on registry date and cause-of-death data) were available. We calculated Kaplan-Meier curves for breast cancer-specific survival and overall survival by stage and analyzed prognostic and treatment factors with a multivariable Cox model. RESULTS: The 2927 incident cases of breast cancer identified in 2002 had the following distribution by stage: stage 0 (in situ), 424 (14%); stage I, 1118 (38%); stage II, 938 (32%); stage III, 233 (8%); stage IV, 123 (4%); unknown, 91 (3%). The distribution of patients' ages was < 40 years, 127 (4%); 40-49, 538 (18%); 50-59, 719 (25%); 60-69, 660 (23%); 70-79, 583 (20%); ≥ 80, 300 (10%). Within the first year after diagnosis, radiotherapy was provided to 1649 patients (56%), chemotherapy to 928 (32%) and hormone therapy to 1664 (57%). Ten-year breast cancer-specific survival rates by stage were > 99% for stage 0, 95% for stage I, 81% for stage II, 55% for stage III and 4% for stage IV. Ten-year overall survival rates were 89% for stage 0, 81% for stage I, 68% for stage II, 43% for stage III and 2% for stage IV. INTERPRETATION: This analysis provides a Canadian benchmark for treatment rates and 10-year outcomes by stage for all incident cases of breast cancer in a single province. Outcomes in British Columbia compared well with published rates for the United States and Europe.
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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".