Gastrointestinal Tract Perineuriomas and Benign Fibroblastic Polyps: Case Report and Comprehensive Systematic Review
Bibliographic record
Abstract
Background: Perineurioma is a rare benign peripheral nerve sheath tumor that can arise in various body locations. In the gastrointestinal (GI) tract, perineuriomas are uncommon and have only been reported in case reports and case series. In addition, a new classification suggests reclassifying benign fibroblastic polyps as perineurioma when they show positive markers of perineurial differentiation. Objective: This study aims to enhance understanding of GI tract perineuriomas by presenting a new case and conducting a systematic literature review. Methods: We described a new case of colonic perineurioma and systematically reviewed all case reports and case series on GI perineuriomas and benign fibroblastic polyps with perineurial markers. We searched ScienceDirect, PubMed/MEDLINE, and Web of Science up to May 2024. Results: A total of 148 cases were analyzed, and most of the cases were published in the last decade (2014–2024). The majority were females (59.46%), with a mean age of 51 years (standard deviation [SD] ±14.87). Most GI perineuriomas (87.5%) were in the distal colon, predominantly in the sigmoid/rectosigmoid (56%) and rectum (14%). Outside the colon, the stomach was the most affected site (7 of 10 cases), with fewer cases in the small intestine and esophagus. The two most commonly performed stains were for epithelial membrane antigen (EMA) and glucose transporter 1 (GLUT‐1), at 75% and 56% of cases, respectively. Noncolonic perineuriomas were generally larger and more symptomatic than colonic ones. Submucosal polyps were more likely symptomatic than mucosal polyps. Conclusion: Perineurioma in the GI tract is a rare benign polyp mainly identified in the distal colon. Its rarity and limited follow‐up data restrict our understanding of recurrence rates. We recommend reporting uncommon polyp locations, detailing polyp morphologies, and using at least two markers for classification.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".