Pancreatic Cancer hENT1 Expression and Survival From Gemcitabine in Patients From the ESPAC-3 Trial
Bibliographic record
Abstract
BACKGROUND: Human equilibrative nucleoside transporter 1 (hENT1) levels in pancreatic adenocarcinoma may predict survival in patients who receive adjuvant gemcitabine after resection. METHODS: Microarrays from 434 patients randomized to chemotherapy in the ESPAC-3 trial (plus controls from ESPAC-1/3) were stained with the 10D7G2 anti-hENT1 antibody. Patients were classified as having high hENT1 expression if the mean H score for their cores was above the overall median H score (48). High and low hENT1-expressing groups were compared using Kaplan-Meier curves, log-rank tests, and Cox proportional hazards models. All statistical tests were two-sided. RESULTS: Three hundred eighty patients (87.6%) and 1808 cores were suitable and included in the final analysis. Median overall survival for gemcitabine-treated patients (n = 176) was 23.4 (95% confidence interval [CI] = 18.3 to 26.0) months vs 23.5 (95% CI = 19.8 to 27.3) months for 176 patients treated with 5-fluorouracil/folinic acid (χ(2) 1=0.24; P = .62). Median survival for patients treated with gemcitabine was 17.1 (95% CI = 14.3 to 23.8) months for those with low hENT1 expression vs 26.2 (95% CI = 21.2 to 31.4) months for those with high hENT1 expression (χ(2)₁= 9.87; P = .002). For the 5-fluorouracil group, median survival was 25.6 (95% CI = 20.1 to 27.9) and 21.9 (95% CI = 16.0 to 28.3) months for those with low and high hENT1 expression, respectively (χ(2)₁ = 0.83; P = .36). hENT1 levels were not predictive of survival for the 28 patients of the observation group (χ(2)₁ = 0.37; P = .54). Multivariable analysis confirmed hENT1 expression as a predictive marker in gemcitabine-treated (Wald χ(2) = 9.16; P = .003) but not 5-fluorouracil-treated (Wald χ(2) = 1.22; P = .27) patients. CONCLUSIONS: Subject to prospective validation, gemcitabine should not be used for patients with low tumor hENT1 expression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".