Patterns of use and outcomes for radiation therapy in the Quality Initiative in Rectal Cancer (QIRC) trial
Bibliographic record
Abstract
BACKGROUND: The Quality Initiative in Rectal Cancer (QIRC) trial targeted surgeon intraoperative technique and not radiation therapy (RT) use. We performed a post hoc analysis of RT use among patients in the QIRC trial, not by arm of trial but rather for the entire group. We wished to identify associations between local recurrence risk and use of preoperative, postoperative or no RT. METHODS: We compared demographic, tumour and process of care measures among patients receiving preoperative, postoperative or no RT. A multivariable Cox regression model assessed local recurrence risk. RESULTS: The QIRC trial enrolled 1015 patients at 16 hospitals between 2002 and 2004. Radiation therapy use did not differ between trial arms, and median follow-up was 3.6 years. For the preoperative, postoperative and no RT groups, respectively, the percentage of patients was 12.8%, 19.3% and 67.9%; the percentage of stage II/III tumours was 57.0%, 88.7% and 48.1%; and the local recurrence rate was 5.3%, 10.2% and 5.5% (p = 0.05). After controlling for patient and tumour characteristics, including tumour stage, the hazard ratio (HR) for local recurrence was increased in the postoperative RT versus the no RT group (HR 1.64, 95% confidence interval 1.04-2.58, p = 0.027). CONCLUSION: Use of preoperative RT was low; most patients with stage II/III disease did not receive RT and, as expected, the postoperative RT group had the highest risk of local recurrence. Our results suggest opportunities to improve rectal cancer RT use in Ontario.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".