Use of a Pan-Canadian indicator to measure treatment rates relative to evidence-based guidelines for rectal cancer.
Bibliographic record
Abstract
177 Background: As part of the Canadian Partnership Against Cancer’s (CPAC) System Performance initiative, indicators measuring treatment practice patterns across the country are now available, offering the ability to compare against evidence-based guidelines. We report on the percentage of patients with stage II and III rectal cancer receiving pre-operative radiation treatment (RT) based on an analysis of Canadian administrative data. A retrospective chart review was conducted to examine reasons for non-treatment with RT, set performance targets, and inform quality improvements. Methods: Data on the percentage of stage II and III rectal cancer cases receiving preoperative RT were obtained from five provincial cancer registries using a standardized methodology for 2,854 cases diagnosed between 2007 and 2008, with 2009 data soon to be available. A retrospective chart review was conducted in five provinces on a random sample of 383 patients diagnosed in 2008 to examine reasons for non-referral and non-treatment. Results: Based on administrative data, an average of 45% of cases received RT preceding surgical resection for stage II or III rectal cancer, ranging from 36% to 48% across provinces. Preoperative RT rates were similar for men and women, but were lower in older patients. From 2007 to 2008, the percentage of patients receiving pre-operative RT increased in all provinces. Results from the chart review showed that, of those who did not receive preoperative RT, 33% were not referred by a surgeon to an oncologist. The most common documented reasons for non-referral were co-morbidities (26%) and patient choice (7%). Among patients referred to an oncologist, 42% were treated with preoperative RT, 30% were treated with post-operative RT and 28% received no treatment. Among those receiving no treatment, 29% were seen only by a medical oncologist, and 18% were not treated due to patient choice. Conclusions: Findings are being used to develop national targets for treatment rates and, working with national oncologist associations, to develop quality improvement strategies, including patient education efforts to promote informed decisions on treatment options.
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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 | 0.009 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".