Colorectal Glandular-Neuroendocrine Mixed Tumor
Bibliographic record
Abstract
Colorectal glandular-neuroendocrine mixed tumor is an uncommon entity with ill-defined clinicopathologic characteristics. We describe the clinicopathology of 23 new cases and review 67 previously reported cases. Clinically, patients (mean age, 61.9 y; male: female, 1.0:1.1) presented with a positive fecal occult blood test or visible rectal bleeding (44%), abdominal pain or change in bowel movement pattern (25%), bowel obstruction (19%), or weight loss (19%). Endoscopically, the tumors presented as a polypoid lesion (57%), a mass lesion (30%), or an ulcerating lesion (9%). Tumors were located in the right colon (56%), transverse colon (3%), and left colon (41%). Surgical resection was the treatment of choice in 83% of cases. After follow-up for an average of 20 months, the tumor-related death rate was 68%. Histologically, 42% were classified as composite tumors and 58% were classified as collision tumors. An adenoma to carcinoma, and then carcinoma to mixed tumor progression through the APC/β-catenin pathway was seen in a majority of cases. Both the glandular and the neuroendocrine components of the mixed tumor can show a spectrum of differentiation, and each component can metastasize separately regardless of its percentage volume. On the basis of the combined analysis of the pathologic spectrum and the clinical behavior of our series and previously reported cases, we propose a new classification system that reflects the differentiation of each component in colorectal glandular-neuroendocrine mixed tumor to facilitate uniform reporting and to better predict its clinical behavior.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".