A POPULATION-BASED STUDY OF FACTORS AFFECTING ACCESS TO RADIOTHERAPY FOR ENDOMETRIAL CANCER IN
Bibliographic record
Abstract
ii Aims: To describe use of post-operative radiation for endometrial cancer in Ontario. To identify system-related and patient-related factors affecting access to this treatment. Materials and Methods: We performed a retrospective population-based cohort study of patients with surgically resected endometrial cancer in the Canadian province of Ontario between 1992-2003. Patients with evidence of incurable cancer at diagnosis or previous cancer diagnosis were excluded. We used multiple logistic regression to assess patient and system factors affecting radiation use. We controlled for disease-related and treatment-related factors: histology, surgical staging, type of hysterectomy and peritoneal biopsy. We applied a mixed model to account for clustering of data by operating hospital. Results: 9,411 women comprised the study cohort. The median age was 63 years. 26.2 % received adjuvant radiation. The proportion of patients receiving radiation varied between cancer centre catchment areas from 18.0 % to 34.3 % (median 26.3%). In multivariate analysis, older patients were more likely to receive radiation up to the age of 80 (p<.0001). Patients who lived further from
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".