Adjuvant chemotherapy for stage II colon cancer: Practice patterns and effectiveness in the general population.
Bibliographic record
Abstract
6569 Background: While guidelines do not recommend adjuvant chemotherapy (ACT) for stage II colon cancer, many state that ACT may be considered in high-risk disease. Here we describe practice patterns and outcomes associated with ACT in the general population. Methods: All cases of colon cancer diagnosed in Ontario 2002-2008 were identified using the Ontario Cancer Registry which was linked to electronic treatment records. Pathology reports were obtained for a 25% random sample of cases. High-risk disease was defined as: T4 tumours, < 12 lymph nodes, poorly differentiated histology, lymphovascular invasion. Modified Poisson regression was used to evaluate factors associated with ACT. Cox proportional hazards model was used to explore the association between ACT and cancer-specific (CSS) and overall (OS) survival. Results: The study population included 2488 patients with stage II colon cancer; 1175 (47%) with high-risk disease. ACT was delivered to 18% of all patients and 24% of patients with high-risk disease. ACT rates were higher among younger patients (51% age 20-49 vs. 16% age 70-79, p < 0.001) and varied considerably across geographic regions (range 10-39%, p < 0.001). Among all patients with stage II colon cancer, ACT was not associated with improved CSS (HR 1.41, 95%CI 1.09-1.82) or OS (HR 1.16, 95%CI 0.94-1.42). Stratified survival analysis for patients with high-risk disease did not show benefit to ACT (CSS HR 1.14, 95%CI 0.84-1.55; OS HR 1.02, 95%CI 0.79-1.31). Conclusions: ACT utilization varies across age groups and geographic regions. ACT is not associated with improved survival among patients with stage II colon cancer including those with high-risk disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".