Prevalence, Risk Factors, and Outcomes of Interval Colorectal Cancers: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: We performed meta-analysis to estimate pooled prevalence, risk factors, and outcomes of interval colorectal cancers (CRCs). METHODS: Systematic literature search through October 2013, identified population-based studies, reporting prevalence of interval CRCs (CRCs diagnosed within 6-36 months of colonoscopy). We estimated the pooled prevalence, patient, endoscopist, and tumor-related risk factors, as well as outcomes of interval CRCs, as compared with detected CRCs (CRCs diagnosed at or within 6 months of colonoscopy). RESULTS: Twelve studies reporting on 7,912 interval CRCs were included. Pooled prevalence of interval CRCs was 3.7% (95% confidence interval (CI)=2.8-4.9%). These cancers were 2.4 times more likely to arise in the proximal colon (6.5%; 95% CI=4.9-8.6%) as compared with distal colon (2.9%; 95% CI=2.0-4.2%). Patients with interval CRCs were older (age >65-70 years vs. <65-70 years: odds ratio (OR)=1.15; 95% CI=1.02-1.30), have more comorbidities (high Charlson comorbidity index: OR=2.00; 95% CI=1.77-2.27), and have diverticular disease (OR=4.25; 95% CI=2.58-7.00). There was a nonsignificant time trend of declining prevalence of interval CRCs from 4.8% in 1990s to 4.2% between 2000 and 2005 and 3.7% beyond 2005. Patients with interval CRCs were less likely to present at an advanced stage (OR=0.79; 95% CI=0.67-0.94), although there was no survival benefit. Considerable heterogeneity was observed in most of the analyses. CONCLUSIONS: Based on meta-analysis, approximately 1 in 27 CRCs are interval CRCs, although the confidence in these estimates is low because of the heterogeneity among the studies. These are more likely to arise in the proximal colon and are diagnosed in older patients, patients with comorbidities or diverticular 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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.021 | 0.059 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".