OC-039 Detection of dysplasia arising in barrett’s oesophagus is improved by trained endoscopists with a specialist interest and dedicated lists
Bibliographic record
Abstract
Introduction Barrett’s oesophagus (BE) is the pre-malignant lesion to oesophageal adenocarcinoma (OAC). The presence of dysplasia, when diagnosed in surveillance programmes, is an important marker of risk of progression and an indication for endoscopic therapy. We have previously demonstrated that BE surveillance technique is variable and suggest centralised lists with few highly trained endoscopists. The aim of this study was to assess the introduction of dedicated BE surveillance lists on dysplasia detection rate (DDR). Method Prospective study of patients undergoing BE surveillance at two hospitals – district general hospital (DGH), and tertiary referral upper GI centre. A group of 4 endoscopists (group A) were trained in Prague classification, Seattle protocol biopsy technique and lesion detection. They were nominated to undertake BE surveillance, with dedicated time slots or lists. The DDR was then compared with historical data from 47 different endoscopists at GSTT (group B) and 24 at UHL (Group C) who had undertaken Barrett’s surveillance over the 5 year period. Analysis was by independent t-tests for continuous variables and chi-squared tests for categorical variables. Results A total of 729 patients with BE underwent endoscopy, between 2007 and 2012. Results are shown in Table 1. There was no significant difference in patient’s age, sex or length of BE between the three groups. Of these, 21% (30/144) were diagnosed with dysplasia/EAC by group A endoscopists vs. 9% (55/587) in Group B/C (p = 0.0004). There was a significant difference in detection rate of Indefinite or Low grade dysplasia (IND/LGD) and High grade dysplasia (HGD)/EAC between the 2 groups. There was a significant difference in diagnosis of IND in community (25/271) vs. teaching hospital (5/458) (p = 0.0001). Documentation of length of BE by Prague criteria was significantly higher in group A than group B&C. The use of High Resolution Endoscopy was similar between both groups. Conclusion This study demonstrates that a group of endoscopists trained in BE surveillance, have significantly higher dysplasia detection rate (DDR) than a non specialist cohort. These findings support the argument that BE surveillance, either at DGH or tertiary centre, should only be carried out on dedicated lists by trained endoscopists with a specialist interest. Disclosure of interest None Declared.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".