The prognostic value of stroma desmoplasia in pancreatic ductal adenocarcinoma.
Bibliographic record
Abstract
211 Background: Pancreatic ductal adenocarcinoma (PDAC) often presents an abundant desmoplastic stroma. We assessed the prognostic value of stroma density and activity in patients with resectable PDAC treated with surgery and adjuvant gemcitabine-based chemotherapy. Methods: FFPE-tissue originating from the pancreatectomy of 145 patients was immunohistochemicallystained for haematoxylin-eosin and Masson’s trichrome to assess stroma density, and alpha-smooth muscle actin (αSMA) expression for activated pancreatic stellate cells. Their expression was correlated with clinicopathological characteristics as well as overall survival (OS), progression-free survival (PFS), local progression-free survival (LPFS) and distant metastases free-survival (DMFS). Results: After a mean follow-up of 20 months (range, 2-69 months), the median OS was 21 months and the 3-year OS was 35.7 %. In multivariate analysis, highly-dense stroma was an independent prognostic parameter for OS (p = 0.001), PFS (p = 0.007), LPFS (p = 0.001) and DMFS (p = 0.002), while αSMA expression lacked significance. Interestingly, highly-dense stroma retained significance for the four clinical endpoints only in early (pT1-2) but not late (pT3-4) stage tumors. Additionally, late pT-stage (pT3-4), the presence of lymph node metastases (pN+ vs pN0), perineural/neural invasion PNI and adjuvant chemotherapy also correlated with prognosis in multivariate analysis. Conclusions: In summary, stroma density represents an independent prognostic marker in PDAC patients treated with adjuvant chemotherapy. Our findings highlight the complexity of desmoplasia and indicate that highly-dense stroma is associated with better outcome. Further validation of the prognostic value of stroma as a biomarker and its role in PDAC biology is warranted and will be performed in a prospective study.
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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 | 0.000 | 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".