HENT1 tumor levels to predict survival of pancreatic ductal adenocarcinoma patients who received adjuvant gemcitabine and adjuvant 5FU on the ESPAC trials.
Bibliographic record
Abstract
4006 Background: Some studies in patients with resected pancreatic cancer have suggested that expression of the human equilibrative nucleoside transporter (hENT1) may be predictive of improved survival from gemcitabine but these have either been based on retrospective non-randomized studies or in one study the principal treatment was chemoradiation. The samples collected from the adjuvant ESPAC1/3 randomized trials have provided a unique opportunity to assess to REMARK standards the therapeutic predictability of hENT1 in patients undergoing resection for pancreatic cancer. Methods: Tissue Microarrays (TMAs) were prepared using paraffin embedded tumor specimens from patients randomized to gemcitabine or 5FU/Folinic acid in the ESPAC-1 and -3 trials. Cores were given an H-Score depending on the level of staining with the 10D7G2 anti-hENT1 antibody. Groups were compared using Kaplan-Meier and Cox proportional hazards. Results: Scores were obtained for 176 gemcitabine treated and 176 5FU treated patients. The overall median H-Score was 48 and patients were classified as having high hENT1 if the mean score for their cores was above this. Median overall survival for gemcitabine treated patients was 23.4 (95% CI: 18.3, 26.0) months versus 23.5 (95% CI: 19.8, 27.3) months for 5FU treated patients (χ21 = 0.24, P = 0.623). In the gemcitabine group A significantly lower survival (χ21 = 9.87, P = 0.002) was noted with low hENT1 (median survival 17.1 (95% CI: 14.3, 23.8) versus 26.2 (95% CI: 21.2, 31.4) months). Median survival was 25.6 (95% CI: 20.1, 27.9) and 21.9 (95% CI: 16.0, 28.3) months respectively for high and low hENT1 in the 5FU group, a non-significant difference (χ21 = 0.83, P = 0.362). Multivariate analysis confirmed hENT1 expression as a predictive marker in gemcitabine (Wald χ2 = 7.10, P = 0.008) but not 5-fluorouracil (Wald χ2 =0.34, P = 0.560) groups. Conclusions: The study supports use of gemcitabine in patients with high tumor hENT1 expression and 5-fluorouracil in patients with low hENT1.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".