Waiting time for radiation therapy in non-metastatic, surgically-treated breast cancer patients in Quebec
Bibliographic record
Abstract
The purpose of this study was to determine among surgically treated non-metastatic breast cancer patients in the province of Quebec the distribution of the time between surgery and post-operative radiation therapy (RT) as well as secular trends and other factors influencing waiting time. Using administrative records, I identified between 1992 and 1998 29,105 episodes of breast cancer and 17,704 of these contained an indication of receiving RT Hierarchical linear regression models were used to identify predictors of waiting time. The number of cases of breast cancer increased by 5.5% per year while the number of those receiving RT increased by 9%. Median post-surgery waiting time was 75 days in 1992 and by 1998 it had increased by 63% (95% Confidence Interval (CI) 35%--97%) among patients not requiring chemotherapy. In patients receiving chemotherapy, post-chemotherapy waiting time increased from 21 to 30 days (35% increase between 1998 and 1992 (95% CI -3%--88%)). In addition to a significant variability of waiting time according to radiation therapy centre, predictors of shorter waiting times were earlier year of treatment, localised cancer stage, breast conserving surgery, early consultation with a radiation oncologist, being operated in a centre with a radiation therapy facility, living close to a radiation therapy facility, and living in a higher socio-economic area. In conclusion, waiting time to start of radiation therapy after localised breast cancer increased substantially in Quebec from 1992 to 1998. Possible explanations include increased demand, insufficient resources and changes in the indications for breast conserving surgery and RT.
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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 | 0.000 | 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 | 0.001 | 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) | 0.002 | 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".