Characteristics Affecting Survival after Locally Advanced Colorectal Cancer in Quebec
Bibliographic record
Abstract
BACKGROUND: We estimated the relations of sociodemographic, organizational, disease, and treatment variables with the risk of death from colorectal cancer (crc) in a Quebec population-based sample of patients with locally advanced crc (lacrc) who underwent tumour resection with curative intent. METHODS: Information from medical records and administrative databases was obtained for a random sample of 633 patients surgically treated for stages ii-iii rectal and stage iii colon cancer and declared to the Quebec cancer registry in 1998 and 2003. We measured personal, disease, and clinical management characteristics, relative survival, and through multivariate modelling, relative excess rate (rer) of death. RESULTS: The relative 5- and 10-year survivals in this cohort were 67.7% [95% confidence interval (ci): 65.8% to 69.6%] and 61.2% (95% ci: 58.3% to 64.0%) respectively. Stage T4, stage N2, and emergency rather than elective surgery affected 18%, 24% and 10% of patients respectively. Those disease progression characteristics each independently increased the rer of death by factors of 2 to almost 5. Grade, vascular invasion, and tumour location were also significantly associated with the rer for death. Receiving guideline-adherent treatment was associated with a 60% reduction in the rer for death (0.41; 95% ci: 0.28 to 0.61), an effect that was consistent across age groups. Clear margins (proximal-distal, radial) and clinical trial enrolment were each associated with a nonsignificant 50% reduction in the rer. Of patients less than 70 years of age and 70 years of age and older, 81.3% and 42.0% respectively received guideline-adherent treatment. CONCLUSIONS: This study is the first Quebec population-based examination of patients with lacrc and their management, outcomes, and outcome determinants. The results can help in planning crc control strategies at a population level.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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, 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".