The incidence of oesophageal adenocarcinoma in non-dysplastic Barrett's oesophagus: a meta-analysis
Bibliographic record
Abstract
INTRODUCTION: The risk of oesophageal adenocarcinoma (OAC) in non-dysplastic Barrett's oesophagus (BO) may have been overestimated. The objective was to estimate the incidence of OAC in patients with BO without dysplasia. METHODS: The authors searched MEDLINE and EMBASE from 1966 to 2011 and performed a bibliographic review of previous publications, excluding abstracts, non-peer-reviewed publications and those not published in English, for prospective or retrospective studies of the incidence of OAC in patients with BO. They excluded patients with any degree of dysplasia at baseline and those without documented intestinal metaplasia. Studies were independently reviewed by two individuals. 57 of 3450 studies were included. The authors extracted information on number of patients with BO, length of follow-up, incident cases of OAC, mean age of patients, country of origin, whether prospective or retrospective, mean length of BO segments and mortality from causes other than OAC. Study quality was assessed by the Ottawa Newcastle criteria. RESULTS: The 57 included studies comprised 11,434 patients and 58,547 patient-years of follow-up. The pooled annual incidence of OAC was 0.33% (95% CI 0.28% to 0.38%). Among 16 studies that provided appropriate information on mortality, there were 56 incident cases of OAC but 684 deaths from apparently unrelated causes. Among 16 studies that provided information on patients with short-segment BO, the annual incidence of OAC was only 0.19%. CONCLUSIONS: The incidence of OAC in non-dysplastic BO is around 1 per 300 patients per year. The incidence of OAC in short-segment BO is under 1 per 500 patients per year.
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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 | 0.018 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.045 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".