Colorectal Cancer Risk Following Adenoma Removal: A Large Prospective Population-Based Cohort Study
Bibliographic record
Abstract
BACKGROUND: Randomized controlled trials have demonstrated significant reductions in colorectal cancer incidence and mortality associated with polypectomy. However, little is known about whether polypectomy is effective at reducing colorectal cancer risk in routine clinical practice. The aim of this investigation was to quantify colorectal cancer risk following polypectomy in a large prospective population-based cohort study. METHODS: Patients with incident colorectal polyps between 2000 and 2005 in Northern Ireland were identified via electronic pathology reports received to the Northern Ireland Cancer Registry. Patients were matched to the Northern Ireland Cancer Registry to detect colorectal cancer and deaths up to December 31, 2010. Colorectal cancer standardized incidence ratios (SIR) were calculated and Cox proportional hazards modeling applied to determine colorectal cancer risk. RESULTS: During 44,724 person-years of follow-up, 193 colorectal cancer cases were diagnosed among 6,972 adenoma patients, representing an annual progression rate of 0.43%. Colorectal cancer risk was significantly elevated in patients who had an adenoma removed (SIR, 2.85; 95% CI, 2.61-3.25) compared with the general population. Male sex, older age, rectal site, and villous architecture were associated with an increased colorectal cancer risk in adenoma patients. Further analysis suggested that not having a full colonoscopy performed at, or following, incident polypectomy contributed to the excess colorectal cancer risk. CONCLUSIONS: Colorectal cancer risk was elevated in individuals following polypectomy for adenoma, outside of screening programs. IMPACT: This finding emphasizes the need for full colonoscopy and adenoma clearance, and appropriate surveillance, after endoscopic diagnosis of adenoma.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".