A Systematic Review of the Histopathology and Immunochemistry in Duodenal Gangliocytic Paragangliomas with Lymph Node Metastases to Identify Predictors of Malignancy
Bibliographic record
Abstract
Gangliocytic paragangliomas (GP) are rare tumors, most commonly located in the 2nd portion of the duodenum.Their origin is poorly understood and management is uncertain.Typically exhibiting benign behavior, they infrequently metastasize to lymph nodes (LN) and distant sites.Due to their triphasic cellular distribution, tissue diagnosis pre-operatively remains a challenge, as well as prediction of which tumors may metastasize or act more aggressively.A systematic literature search was performed, and data for epidemiology, clinical history, gross pathology, and histopathology of duodenal (DGPs) with LN metastases was collected.Histopathology and Immunohistochemistry (IHC) was described and compared to a review by Okubo et al in an effort to identify predictors of malignancy.It is difficult to obtain a tissue diagnosis and predict malignant behavior of DGPs.Increased tumor size, depth of invasion, angio-lymphatic invasion and IHC findings may warrant further investigation for LN metastases.The presence of LN metastases does not seem to influence the prognosis, but rather the treatment modality.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".