Hormone profiling, <scp>WHO</scp> 2010 grading, and <scp>AJCC</scp>/<scp>UICC</scp> staging in pancreatic neuroendocrine tumor behavior
Bibliographic record
Abstract
Pancreatic neuroendocrine tumors (pNETs) are the second most common pancreatic neoplasms, exhibiting a complex spectrum of clinical behaviors. To examine the clinico-pathological characteristics associated with long-term prognosis we reviewed 119 patients with pNETs treated in a tertiary referral center using the WHO 2010 grading and the American Joint Committee on Cancer/International Union Against Cancer (AJCC/UICC) staging systems, with a median follow-up of 38 months. Tumor size, immunohistochemistry (IHC) profiling and patient characteristics-determining stage were analyzed. Primary clinical outcomes were disease progression or death. The mean age at presentation was 52 years; 55% were female patients, 11% were associated with MEN1 (multiple endocrine neoplasia 1) or VHL (Von Hippel-Lindau); mean tumor diameter was 3.3 cm (standard deviation, SD) (2.92). The clinical presentation was incidental in 39% with endocrine hypersecretion syndromes in only 24% of cases. Nevertheless, endocrine hormone tissue immunoreactivity was identified in 67 (56.3%) cases. According to WHO 2010 grading, 50 (42%), 38 (31.9%), and 3 (2.5%) of tumors were low grade (G1), intermediate grade (G2), and high grade (G3), respectively. Disease progression occurred more frequently in higher WHO grades (G1: 6%, G2: 10.5%, G3: 67%, P = 0.026) and in more advanced AJCC stages (I: 2%, IV: 63%, P = 0.033). Shorter progression free survival (PFS) was noted in higher grades (G3 vs. G2; 21 vs. 144 months; P = 0.015) and in more advanced AJCC stages (stage I: 218 months, IV: 24 months, P < 0.001). Liver involvement (20 vs. 173 months, P < 0.001) or histologically positive lymph nodes (33 vs. 208 months, P < 0.001) were independently associated with shorter PFS. Conversely, tissue endocrine hormone immunoreactivity, independent of circulating levels was significantly associated with less aggressive disease. Age, gender, number of primary tumors, and heredity were not significantly associated with prognosis. Although the AJCC staging and WHO 2010 grading systems are useful in predicting disease progression, tissue endocrine hormone profiling provides additional information of potentially important prognostic value.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".