Predictors of dysplastic and neoplastic progression of Barrett’s esophagus
Bibliographic record
Abstract
Background: It is unknown why some cases of Barrett’s esophagus progress to invasive malignant disease rapidly while others do so more slowly or not at all. The aim of this study was to identify demographic and endoscopic factors that predict dysplastic and neoplastic progression in patients with Barrett’s esophagus. Methods: Patients with Barrett’s esophagus who were assessed in 2000–2010 were assessed for inclusion in this retrospective study. Demographic and endoscopic variables were collected from an endoscopy database and the medical chart. Dysplastic and neoplastic progression was examined by time-to-event analysis. We used Cox proportional hazard regression modelling and generalized estimating equation methods to identify variables that were most predictive of neoplastic progression. Results: A total of 518 patients had Barrett’s esophagus confirmed by endoscopy and pathology and at least 2 surveillance visits. Longer Barrett’s esophagus segment (≥ 3 cm) (odds ratio [OR] 1.2, 95% confidence interval [CI] 1.1–1.3) and increased age (≥ 60 yr) (OR 3.5, 95% CI 1.7–7.4) were independent predictors of progression from nondysplasia to dysplastic or neoplastic grades. Presence of mucosal irregularities (OR 8.6, 95% CI 2.4–30.4) and increased age (OR 5.1, 95% CI 1.6–16.6) were independent predictors of progression from nondysplasia to high-grade dysplasia or adenocarcinoma. Conclusion: Increased age, longer Barrett’s segment and presence of mucosal irregularities were associated with increased risk of dysplastic and neoplastic progression. In addition to dysplasia, these factors may help stratify patients according to risk of neoplastic progression and be used to individualize surveillance. More prospective studies with larger samples are required to validate these results.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".