Prognostic value of an immune score combining intra- and peritumoral T-cell subset density in patients with pancreatic adenocarcinoma.
Bibliographic record
Abstract
4060 Background: Immune scoring based on T-cell subsets and density can add prognostic value to conventional TNM staging for patients with solid tumors, but limited data are available for pancreatic adenocarcinoma. Methods: Using tissue microarrays, CD3, CD4, CD8, CD45RO, and FOXP3 T-cells were quantified by immunohistochemistry in the intratumoral (IT) compartment and peritumoral (PT) parenchyma of 111 consecutively resected specimens. T-cell counts were correlated with patient overall survival, disease-free survival, and time to recurrence (OS, DFS, TTR) by Cox regression, controlling for clinicopathological factors. An immune score (IS) based on IT CD4 T-cell count > median, PT CD8 T-cell count ≤ median, and IT/PT CD3 T-cell ratio >1, grouped patients into high, intermediate, or low categories if all 3, 1 to 2, or none of these immune features were present, respectively. Results: Median follow-up time was 20 months, and 85% of patients either died or recurred during the study period. By univariate analysis, PT CD8 T-cell count was associated with shorter OS (p=0.02), whereas both IT CD4 T-cell count and IT/PT CD3 T-cell ratio were associated with longer OS (p=0.01 and p=0.05, respectively). Alone, none of these immune features predicted TTR. Combined into an IS, patients in the high (n=23), intermediate (n=60), or low (n=23) categories had significantly different OS (respective medians 30, 17, and 13 months, log-rank p=0.01), DFS (28, 16, and 12 months, p=0.01), and TTR (21, 14, and 10 months, p=0.02). By multivariate analysis, the association between IS and clinical outcomes was independent of tumor size, extra-pancreatic invasion, and nodal metastases (TNM staging). The IS discriminated outcomes among patients with nodal metastases (n=80), such that node-positive patients with a high IS had a median survival similar to node-negative patients (30 and 33 months, p=0.7). FOXP3 and CD45RO T-cell counts did not appear to add prognostic value to the IS. Conclusions: An immune score that combines specific T-cell location and density may have prognostic value in patients with resected pancreatic adenocarcinoma, independently from pathologic features currently used for staging.
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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".