Adherence to post-polypectomy surveillance guidelines: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) is a major worldwide cause of cancer-related mortality. Colonoscopy programs based on guideline-recommended surveillance intervals have been put in place to reduce the morbidity and mortality associated with CRC. We were interested to evaluate clinical practice adherence to guideline-recommended surveillance intervals, the potential extent of early repeat colonoscopies, and causes of nonadherence to guideline recommendations. METHODS: We performed a literature search for articles reporting on guideline adherence for surveillance colonoscopies. Exclusion criteria included inflammatory bowel disease and hereditary CRC syndrome cohorts. Primary outcome was correct interval assignment in patients undergoing surveillance colonoscopy. Groups were assessed for adherence according to their respective guideline recommendations (North American or European). RESULTS: 16 studies were included in the analysis. The mean colonoscopy surveillance interval adherence rate was 48.8 % (95 % confidence interval [CI] 37.3 - 60.4). For North American guidelines, surveillance interval assignments were adherent to guideline recommendations in 44.7 % (95 %CI 24.2 - 66.3) of patients after detection of low risk lesions and in 54.6 % (95 %CI 41.4 - 67.4) after detection of high risk lesions. For European guidelines, surveillance interval assignments were adherent to recommendations in 24.4 % (95 %CI 1.1 - 63.4) of patients after detection of low risk lesions and in 73.6 % (95 %CI 35.5 - 98.8) after detection of high risk lesions. CONCLUSIONS: The worldwide adherence to surveillance colonoscopy guidelines was low, with more than 50 % of patients undergoing repeat colonoscopies either too early or too late. Early repeat colonoscopies occurred with the highest frequency for patients in whom only hyperplastic polyps or low risk adenomas were found.
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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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.028 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".