A107 WHAT SIZE CUT-OFF LEVEL SHOULD BE USED TO IMPLEMENT OPTICAL POLYP DIAGNOSIS?
Bibliographic record
Abstract
Abstract Background The risk of advanced pathology and potential mismanagement increases with polyp size while performing optical diagnosis. We hypothesized that a lower polyp size cut-off (e.g., 1–3 mm) would be associated with a lower risk of misclassifying advanced neoplasia or even cancer when using optical diagnosis. Aims This study aimed to evaluate the proportion of patients undergoing inadequate surveillance intervals associated with different size cut-offs when using optical diagnosis. Methods In a post-hoc analysis of three prospective studies, the use of optical diagnosis was evaluated for three polyp size groups: 1–3, 1–5, and 1–10 mm. The primary outcome was the proportion of patients in which advanced adenomas were found and optical diagnosis resulted in delayed surveillance in each group. Secondary outcomes included agreements between surveillance intervals based on high-confidence optical diagnosis and pathology outcomes, reduction in histopathological examinations, and proportion of patients who could receive an immediate surveillance recommendation. Results We included 3374 patients (7291 polyps ≤10 mm) undergoing complete colonoscopies (median age 66.0 years, 75.2% male, 29.6% for screening). Among polyp sized 1–3 mm, 1–5 mm, and 1–10 mm, 0.5%, 0.6%, and 1.2% of polyps, respectively, were found to have advanced pathology ( P <.0001). The percentage of patients with advanced adenomas and either 2- or 7- year delayed surveillance intervals (n=79) was 3.8%, 15.2%, and 25.3% for size cut-offs of 1–3, 1–5, and 1–10 mm polyps, respectively ( P<.0001). Surveillance interval agreements between pathology and high-confidence optical diagnosis for the three groups were 97.2%, 95.5%, and 94.2%, respectively. In the cohort of patients in which patients with normal colonoscopy, polyps >10 mm, and poor bowel preparation were excluded, the surveillance interval agreements between pathology and high-confidence optical diagnosis for the three groups were 96.2%, 93.6%, and 92.1%, respectively. Total reduction in pathology examinations for the three groups were 33.5%, 62.3%, and 78.2%, respectively. Furthermore, optical diagnosis could have allowed 41.0%, 58.2%, and 73.3% of patients, respectively, to be given immediate surveillance interval recommendations. Conclusions This study showed that limiting optical diagnosis to polyps 1–3 mm resulted in an excellent safety profile with a very low risk for inappropriate management of advanced adenomas, which makes routine clinical implementation of the “resect and discard” strategy feasible. Implementing a 3 mm cut-off could be a starting point for endoscopists to feel comfortable with the “resect and discard” strategy, with the potential of implementing a 5 mm cut-off, once optical diagnosis becomes more popular, and endoscopists become more comfortable with its use. Funding Agencies NoneNA
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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 | 0.009 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".