The Spectrum of Neuroendocrine Differentiation Among Gastrointestinal Carcinoids
Bibliographic record
Abstract
CONTEXT: The advent of panneuroendocrine markers has helped to better depict the heterogeneity of gastrointestinal carcinoids. Consequently, it has been proposed that these tumors constitute a histologic spectrum that includes well-, moderately, and poorly differentiated carcinoids. However, the reproducibility of this grading system and its prognostic importance have sometimes been called into question. OBJECTIVE: To investigate the potential utility of cell proliferation and oncoprotein markers in augmenting the histologic classification. DESIGN AND SETTING: Retrospective study; tertiary care teaching hospital. METHODS: Fifty-eight patients with 41 well-differentiated, 12 moderately differentiated and 5 poorly differentiated carcinoids from various topographic sites of the gastrointestinal tract were selected and immunostained for panneuroendocrine markers, MIB-1, p53, and bcl-2. MAIN OUTCOME MEASURES: Degree of association between histologic grading, MIB-1, p53, and bcl-2 immunoreactivity and carcinoid metastatic behavior. RESULTS: The group comprised 30 males and 28 females whose mean age was 52.7 years (range, 14-81). Mean follow-up time was 85.8 months. All 58 patients tested positive for chromogranin A and/or synaptophysin. The group was divided into nonmetastatic (42/58, or 72.4%) and metastatic (16/58, or 27.6%) cases. Histologic grading tended to be associated with metastatic spread, but this occurrence of metastases did not attain statistical significance (P =.08). Positivity for MIB-1 (P =.004) and p53 (P =.04) was significantly associated with metastatic behavior, whereas bcl-2 was not (P = 0. 63). CONCLUSIONS: Although an organoid pattern and neuroendocrine immunophenotype help to define the spectrum of gastrotestinal carcinoids, this study suggests that the histologic grading of these tumors has some limitations with respect to predicting metastatic behavior. However, MIB-1 and p53 can compliment histologic grading as prognostic indicators in this regard while bcl-2 appears to be less useful.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".