Relationship between the polyp detection rate and the post-colonoscopy colorectal cancer rate
Bibliographic record
Abstract
AIM: the adenoma detection rate is the quality indicator of colonoscopy that is most closely related to the development of interval colorectal cancer or post-colonoscopy colorectal cancer. However, the recording of this indicator in different units of gastrointestinal endoscopy is obstructed due to the large consumption of resources required for its calculation. Several alternatives have been proposed, such as the polyp detection rate. The objective of this study was to evaluate the relationship between the polyp detection rate and its influence on post-colonoscopy colorectal cancer rate. PATIENTS AND METHODS: in this study, 12,482 colonoscopies conducted by 14 endoscopists were analyzed. The polyp detection rate was calculated for each endoscopist. Endoscopists were grouped into quartiles (Q1, Q2, Q3, and Q4), from lowest to highest polyp detection rate, in order to evaluate whether there were any differences in the development of post-colonoscopy colorectal cancer. RESULTS: the lowest polyp detection rate was 20.66% and the highest was 52.16%, with a median of 32.78 and a standard deviation of ± 8.54. A strong and positive association between polyp endoscopy diagnosis and adenoma histopathology result was observed and a linear regression was performed. A significantly higher post-colonoscopy colorectal cancer rate was observed in the group of endoscopists with a lower polyp detection rate (p < 0.02). CONCLUSION: polyp detection rate is a valuable quality indicator of colonoscopy and its calculation is much simpler than that of the adenoma detection rate. In our study, the prevalence of post-colonoscopy colorectal cancer was inversely and significantly related to the endoscopists' polyp detection rate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".