Expression of dihydropyrimidine dehydrogenase (DPD) and hENT1 predicts survival in pancreatic cancer
Bibliographic record
Abstract
BACKGROUND: Dihydropyrimidine dehydrogenase (DPD) tumour expression may provide added value to human equilibrative nucleoside transporter-1 (hENT1) tumour expression in predicting survival following pyrimidine-based adjuvant chemotherapy. METHODS: DPD and hENT1 immunohistochemistry and scoring was completed on tumour cores from 238 patients with pancreatic cancer in the ESPAC-3(v2) trial, randomised to either postoperative gemcitabine or 5-fluorouracil/folinic acid (5FU/FA). RESULTS: DPD tumour expression was associated with reduced overall survival (hazard ratio, HR = 1.73 [95% confidence interval, CI = 1.21-2.49], p = 0.003). This was significant in the 5FU/FA arm (HR = 2.07 [95% CI = 1.22-3.53], p = 0.007), but not in the gemcitabine arm (HR = 1.47 [0.91-3.37], p = 0.119). High hENT1 tumour expression was associated with increased survival in gemcitabine treated (HR = 0.56 [0.38-0.82], p = 0.003) but not in 5FU/FA treated patients (HR = 1.19 [0.80-1.78], p = 0.390). In patients with low hENT1 tumour expression, high DPD tumour expression was associated with a worse median [95% CI] survival in the 5FU/FA arm (9.7 [5.3-30.4] vs 29.2 [19.5-41.9] months, p = 0.002) but not in the gemcitabine arm (14.0 [9.1-15.7] vs. 18.0 [7.6-15.3] months, p = 1.000). The interaction of treatment arm and DPD expression was not significant (p = 0.303), but the interaction of treatment arm and hENT1 expression was (p = 0.009). CONCLUSION: DPD tumour expression was a negative prognostic biomarker. Together with tumour expression of hENT1, DPD tumour expression defined patient subgroups that might benefit from either postoperative 5FU/FA or gemcitabine.
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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 | 0.001 | 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".