Immunophenotyping of ampullary carcinomata allows for stratification of treatment specific subgroups
Bibliographic record
Abstract
BACKGROUND: Ampullary carcinomata (AC) can be separated into intestinal (IT) or pancreatobiliary (PB) subtypes. Although morphological, immunohistochemical and molecular differentiation of IT and PB have been well documented; the prognostic significance of histological subtype and whether patients with either subtype benefit from differential chemotherapeutic regimens remains unclear. METHODS: As part of a larger cohort study, patients who underwent resection for AC or pancreatic ductal adenocarcinoma (PDAC) were retrospectively identified. Clinicopathological covariates and outcome were obtained and MUC1, MUC2, CDX2 and CK20 were assessed with immunohistochemistry. RESULTS: Of 99 ACs, the resultant immunophenotypes indicated 48% and 22% were IT and PB, respectively. Thirty (30%) cases were quadruple negative (QN). Within the PDAC cohort (N = 257), the most prevalent immunophenotype was QN (53%). Subsequently, all QN ACs were classified as PB immunohistochemically yielding 47.5% and 52.5% classified as IT and PB, respectively. Involved regional lymph nodes and elevated T-stage were significantly associated with PB compared with IT AC (p = 0.0032 and 0.0396, respectively). Progression-free survival revealed inferior survival for PB versus IT AC (p = 0.0156). CONCLUSIONS: AC can be classified into prognostic groups with unique clinicopathological characteristics using immunohistochemistry. Immunophenotypical similarity of PB and PDAC suggests that treatment regimens similar to those used in PDAC should be explored.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".