Management of Barrett's Esophagus in the UK: Overtreated and Underbiopsied but Improved by the Introduction of a National Randomized Trial
Bibliographic record
Abstract
OBJECTIVES: To assess the variation in practice of Barrett's esophagus (BE) management in comparison with accepted international guidelines before and after the introduction of a large BE randomized controlled trial (RCT) with protocols including those of tissue sampling. DESIGN: A validated anonymized questionnaire was sent to 401 senior attending gastroenterologists asking for details of their current management of BE, especially histological sampling. Of the 228 respondents, 57 individuals (each from a different center) were in the first group to enter the ASPirin Esomeprazole (BE) Chemoprevention Trial (AspECT), and we assessed change in practice in these centers. RESULTS: Ninety percent of specialists did not take adequate biopsies for histological diagnosis. Furthermore, 74% would consider aggressive surgical resection for prevalent cases of high-grade dysplasia in BE as their first-line choice despite the associated perioperative mortality. Ninety-two percent claim their lack of adherence to guidelines is because there is a need for stronger evidence for surveillance and medical interventions. Effect of the AspECT trial: Those clinicians in centers where the AspECT trial has started have improved adherence to ACG guidelines compared with their previous practice (P < 0.05). BE patients now get 18.8% more biopsies compared with previous practice, and 37.7% if the patient is entered into the AspECT trial (P < 0.01). CONCLUSIONS: This large study indicates both wide variation in practice and poor compliance with guidelines. Because optimal histology is arguably the most important facet of BE management, the improvement in practice in centers taking part in the AspECT trial indicates an additional value of large international RCTs.
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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 | 0.035 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".