Tumor Budding Is an Independent Adverse Prognostic Factor in Pancreatic Ductal Adenocarcinoma
Bibliographic record
Abstract
Tumor budding is a well-established adverse prognostic factor in colorectal cancer. However, the significance and diagnostic reproducibility of budding in pancreatic carcinoma requires further study. We aimed to assess the prognostic significance of tumor budding in pancreatic ductal adenocarcinoma, determine its relationship with other clinicopathologic features, and assess interobserver variability in its diagnosis. Tumor budding was assessed in 192 archival cases of pancreatic ductal adenocarcinoma using hematoxylin and eosin (H&E) sections; tumor buds were defined as single cells or nonglandular clusters composed of <5 cells. The presence of budding was determined through assessment of all tumor-containing slides, and associations with clinicopathologic features and outcomes were analyzed. Six gastrointestinal pathologists participated in an interobserver variability study of 120 images of consecutive tumor slides stained with H&E and cytokeratin. Budding was present in 168 of 192 cases and was associated with decreased overall survival (P=0.001). On multivariable analysis, tumor budding was prognostically significantly independent of stage, grade, tumor size, nodal status, lymphovascular invasion, and perineural invasion. There was substantial agreement among pathologists in assessing the presence of tumor budding using both H&E (K=0.63) and cytokeratin (K=0.63) stains. The presence of tumor budding is an independent adverse prognostic factor in pancreatic ductal carcinoma. The assessment of budding with H&E is reliable and could be used to better risk stratify patients with pancreatic ductal adenocarcinoma.
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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 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".