Worldwide Esophageal Cancer Collaboration: clinical staging data
Bibliographic record
Abstract
To address uncertainty of whether clinical stage groupings (cTNM) for esophageal cancer share prognostic implications with pathologic groupings after esophagectomy alone (pTNM), we report data—simple descriptions of patient characteristics, cancer categories, and non–risk-adjusted survival—for clinically staged patients from the Worldwide Esophageal Cancer Collaboration (WECC). Thirty-three institutions from six continents submitted data using variables with standard definitions: demographics, comorbidities, clinical cancer categories, and all-cause mortality from first management decision. Of 22,123 clinically staged patients, 8,156 had squamous cell carcinoma, 13,814 adenocarcinoma, 116 adenosquamous carcinoma, and 37 undifferentiated carcinoma. Patients were older (62 years) men (80%) with normal body mass index (18.5–25 mg/kg2, 47%), little weight loss (2.4 ± 7.8 kg), 0-1 ECOG performance status (67%), and history of smoking (67%). Cancers were cT1 (12%), cT2 (22%), cT3 (56%), cN0 (44%), cM0 (95%), and cG2-G3 (89%); most involved the distal esophagus (73%). Non–risk-adjusted survival for squamous cell carcinoma was not distinctive for early cT or cN; for adenocarcinoma, it was distinctive for early versus advanced cT and for cN0 versus cN+. Patients with early cancers had worse survival and those with advanced cancers better survival than expected from equivalent pathologic categories based on prior WECC pathologic data. Thus, clinical and pathologic categories do not share prognostic implications. This makes clinically based treatment decisions difficult and pre-treatment prognostication inaccurate. These data will be the basis for the 8th edition cancer staging manuals following risk adjustment for patient characteristics, cancer categories, and treatment characteristics and should direct 9th edition data collection.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.018 |
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".