Clinical characteristics of young patients with early Barrett’s neoplasia
Bibliographic record
Abstract
BACKGROUND: Esophageal adenocarcinoma (EAC) and high-grade dysplasia (HGD) may appear in young patients with Barrett's esophagus (BE). However, characteristics of Barrett's-related neoplasia in this younger population remain unknown. AIM: To identify clinical characteristics that differ between young and old patients with early-stage Barrett's-related neoplasia. METHODS: We conducted a retrospective analysis of a prospectively maintained database comprised of consecutive patients with early-stage EAC (pT1) and HGD at a tertiary-referral center between 2001 and 2017. Baseline characteristics, drug and risk factor exposures, clinicopathological staging of EAC/HGD and treatment outcomes [complete eradication of neoplasia (CE-N), complete eradication of intestinal metaplasia (CE-IM), recurrence of neoplasia and recurrence of intestinal metaplasia] were retrieved. Multivariate analyses were performed to identify factors that differed significantly between older and younger (≤ 50 years) patients. RESULTS: < 0.01) compared to the old group. However, there were no significant differences regarding tumor histology, CE-N, CE-IM, recurrence of neoplasia and recurrence of intestinal metaplasia (mean follow-up, 44.3 mo). CONCLUSION: While guidelines recommend BE screening in patients > 50 years of age, younger patients should be considered for screening endoscopy if they suffer from obesity and GERD symptoms.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".