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 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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".