Rate and Predictors of Early/Missed Colorectal Cancers After Colonoscopy in Manitoba: A Population-Based Study
Bibliographic record
Abstract
OBJECTIVES: Many of the colorectal cancers (CRCs) diagnosed within 3 years after a colonoscopy are likely because of lesions missed on the initial colonoscopy. In this population-based study, we investigated the rate and predictors of CRCs diagnosed within 3 years of a colonoscopy. METHODS: We identified individuals 50-80 years of age diagnosed with CRC between 1992 and 2008 from the provincewide Manitoba Cancer Registry. Performance of colonoscopy and history of co-morbidities was determined by linkage to the provincial universal health care insurance provider's physician billing claims and hospital discharges databases. CRCs diagnosed within 6 months of a colonoscopy were categorized as detected CRCs and those 6-36 months after a colonoscopy as early/missed CRCs. Logistic regression analysis was performed to identify the patient, endoscopist, colonoscopy, and CRC factors associated with early/missed CRCs. RESULTS: Of the 4,883 CRCs included in the study, 388 (7.9%) were early/missed CRCs, with a range of 4.5% of rectum/rectosigmoid cancers in men to 14.4% of transverse colon/splenic flexure cancers in women. Independent risk factors associated with early/missed CRCs included prior colonoscopy, performance of index colonoscopy by family physicians, recent year of CRC diagnosis, and proximal site of CRC. CONCLUSIONS: This study suggests that approximately 1 in 13 CRCs may be an early/missed CRC, diagnosed after an index colonoscopy in usual clinical practice. Women are more likely to have early/missed CRC. It is unclear if this relates to differences in procedure difficulty, bowel preparation issues, or tumor biology between men and women.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".