Use and Effectiveness of Adjuvant Chemotherapy for Stage III Colon Cancer: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: International guidelines recommend adjuvant chemotherapy (ACT) for patients with stage III colon cancer. Whether efficacy observed in clinical trials translates to effectiveness in routine practice is less well understood. Here we describe use and outcomes of ACT in routine practice. METHODS: All cases of colon cancer treated with surgery in Ontario 2002-2008 were identified using the population-based Ontario Cancer Registry. Linked electronic records of treatment identified surgery and ACT use. Pathology reports were obtained for a random 25% sample of all cases; patients with stage III disease were included in the study population. Modified Poisson regression was used to evaluate factors associated with ACT. Cox proportional hazards model and propensity score analysis were used to explore the association between ACT and cancer-specific survival (CSS) and overall survival (OS). RESULTS: The study population included 2,801 patients with stage III colon cancer; 66% (n=1,861) received ACT. ACT use rates varied substantially across age groups; 90% among patients aged 20 to 49 years versus 68% among those aged 70 to 79 years (P<.001). ACT use was inversely associated with comorbidity (P<.001) and socioeconomic status (P=.049). In adjusted analyses advanced age is associated with inferior CSS and OS. Use of ACT was associated with decreased risk of death from cancer (hazard ratio [HR], 0.63; 95% CI, 0.54-0.73) and decreased risk of death from any cause (HR, 0.63; 95% CI, 0.55-0.71). This result was consistent in the propensity score analysis. CONCLUSIONS: One-third of patients with stage III colon cancer in the general population do not receive ACT. Use of ACT in routine practice is associated with a substantial improvement in CSS and OS.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".