Treatment of squamous cell and adenocarcinoma of the esophagus
Bibliographic record
Abstract
Barrie Rathbone,1 Janusz Jankowski,2 Michael Rathbone31University Hospitals of Leicester, Leicester, 2Sir James Black Professor Queen Mary University of London, 3St George's University of London, London, United KingdomAbstract: Esophageal cancer is the sixth commonest cause of cancer death worldwide. It predominantly occurs in two histological types, ie, squamous cell carcinoma and adenocarcinoma, each with its own distinct geographical distribution and natural history. The incidence of esophageal adenocarcinoma is rising, as is that of its precursor lesion, Barrett's esophagus, which consists of metaplastic change in the squamous mucosa of the esophagus in response to damage by gastroesophageal reflux disease. The principal risk factors for esophageal cancer are cigarette smoking and alcohol consumption, reflux disease, and obesity. In tumors without local invasion or distant metastases, surgery remains the treatment option of choice, although there are considerable differences of opinion regarding the roles of chemotherapy and radiotherapy. A wide variety of endoscopic treatments are available for dysplastic lesions and palliation. Despite the availability of increasingly complex imaging modalities and expensive and possibly ineffective attempts at screening, the evidence base is conflicted and the prognosis remains poor. However, from a recent large systematic review, three clear recommendations can be made, ie, use of endoscopic resection for high grade dysplasia, use of radiofrequency ablation for residual premalignant lesions, and, finally, prevention of risk factors for cancer, such as smoking, alcohol consumption, and obesity.Keywords: cancer, Barrett's, esophagus, squamous cell carcinoma, adenocarcinoma
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".