Population-Based Utilization of Radiation Therapy by a Canadian Breast Cancer Cohort
Bibliographic record
Abstract
We examined trends in radiation therapy (rt) utilization by a population-based breast cancer cohort in Ontario. The provincial cancer registry provided a breast cancer cohort based on diagnosis dates from April 1, 2005, to March 31, 2010. Staging information was also available. The cohort was then linked, by encrypted health card number, to linkable administrative datasets, including rt utilization. The average age in the identified female breast cancer cohort (n = 39,656) was 61.6 ± 14.0 years. Almost two thirds of the patients (n = 25,225) received rt, and staging information was available for 22,988 patients (9541 stage i, 8516 stage ii, 4050 stage iii, and 881 stage iv). The average number of rt courses received by the patients was 1.4 ± 0.7 for stage i, 1.8 ± 1.1 for stage ii, 2.5 ± 1.3 for stage iii, and 2.8 ± 2.4 for stage iv. The ratio of conventional rt to intensity-modulated rt was 70.9%:16.6% for stage i, 71.6%:11.3% for stage ii, 74.6%:4.6% for stage iii, and 89.6%:2.2% for stage iv. From 2005 to 2010, almost two thirds of a Canadian female breast cancer cohort received rt, and the average number of courses increased with disease severity. A similar trend was observed with the type of rt (use of conventional rt increased with disease severity). The next step is to apply unit costs to the number of fractions and to obtain rt planning and radiation therapist times.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| 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".