Breast cancer survival by teaching status of the initial treating hospital.
Bibliographic record
Abstract
BACKGROUND: A number of studies have documented variation in treatment patterns by treatment setting or by region. In order to better understand how treatment setting might affect survival, we compared the survival outcomes of women with node-negative breast cancer who were initially treated at teaching hospitals with those of women initially treated at community hospitals. METHODS: We constructed a retrospective cohort consisting of a random sample of 938 cases, initially diagnosed in 1991, drawn from the Ontario Cancer Registry. Exposure was defined by the type of hospital in which the initial breast cancer surgery was performed. Outcomes were ascertained through follow-up of vital statistics. RESULTS: The crude 5-year survival rate was 88.7% for women who had their initial surgery in a community hospital and 92.5% for women who had their initial surgery in a teaching hospital. Women in higher income neighbourhoods experienced better survival at 5 years regardless of which type of hospital they were treated in. Multivariate proportional hazards regression modelling demonstrated a 53% relative reduction in risk of death among women with tumours less than or equal to 20 mm in diameter who were treated at a teaching hospital (relative risk [RR] = 0.47, 95% confidence interval [CI] 0.23-0.96), whereas among those with larger tumours there was no demonstrated difference in survival (RR = 1.32, 95% CI 0.73-2.32). Other variables that were significant in the model were age at diagnosis, estrogen receptor status and the use of radiation therapy. INTERPRETATION: Women with node-negative breast cancer and tumours less than or equal to 20 mm in diameter who were initially seen at a teaching hospital had significantly better survival than women with similar tumours who were initially seen at a community hospital. Survival among women with larger tumours was not statistically significantly different for the 2 types of hospital.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".