Thymidylate synthase and thymidine phosphorylase expression in resected colorectal liver metastases do not predict overall survival nor response to chemotherapy
Bibliographic record
Abstract
3605 Background: Enzyme expression has been reported to be of both predictive and prognostic significance in patients with colorectal liver metastases (CLM). We determined whether thymidylate synthase (TS) and/or thymidine phosphorylase (TP) can be used to determine the prognosis of patients with CLM who have undergone potentially curative hepatic resection and whether TS and/or TP status can be used to predict which patients would be likely to benefit from (neo)adjuvant chemotherapy. Methods: Paraffin tumor blocks from 99 patients who received potentially curative liver resections for CLM were evaluated. TS and TP expression were assessed by immunohistochemistry (IHC) assays. Overall survival (OS) and disease-free survival (DFS) were compared between high and low expressors of TS and TP singly and in combination. The predictive value for response to (neo)adjuvant chemotherapy of TS alone as well as the TS / TP combination were evaluated. Results: Median OS for the TS+ group (n=47) was 4.51 years and DFS was 2.37 years, which were not significantly different from those of the TS- group (n=52): 4.05 years and 1.14 years (p=0.44 and p=0.10). Similarly, TS status did not predict the differential effects of (neo)adjuvant chemotherapy on OS (TS- p = 0.72, TS+ p = 0.49) or DFS (TS- p = 0.91, TS+ p = 0.28). Median OS for the TP+ group (n=10) was 4.35 years and DFS was 0.50 years, which were not significantly different from those of the TP- group (n=89): 4.05 years and 1.52 years (p=0.66 and p=0.24). TS/TP- tumors did not demonstrate improved OS (4.04 vs 4.51 years; p = 0.47) or DFS (1.20 years vs 1.96 years; p = 0.17). Similarly, TS/TP status did not predict the differential effects of (neo)adjuvant chemotherapy on OS (TS/TP- p = 0.73, TS/TP+ p = 0.67) or DFS (TS/TP- p = 0.95, TS/TP+ p = 0.40) Conclusions: TS and TP individually or in combination as measured using IHC appear not to be important prognostic indicators of OS or DFS in patients who underwent potentially curative liver resections for CLM. In addition these classifications can not be used to predict the differential effects of (neo)adjuvant chemotherapy in these patients. No significant financial relationships to disclose.
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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".