Preoperative serum artemin (ARTN) as a predictive biomarker of recurrence following curative resection for hepatocellular carcinoma (HCC).
Bibliographic record
Abstract
571 Background: Tumor-induced generation of splenic erythroblast- like cells (Ter-cells) has been shown to promote tumor progression. These Ter-cells produce the glial-line derived neurotropic factor, ARTN. We investigated the association of pre-operative serum ARTN and the risk of recurrence in HCC patients (pts) undergoing curative resection. Methods: Blood samples were collected prior to surgery as part of an institutional molecular epidemiologic study. Serum ARTN concentration was measured using an enzyme-linked immunosorbent assay (ELISA). Demographics, pathological variables known to be associated with outcomes and clinical outcomes were collected. Uni- and multi-variate analysis were conducted. The optimal cutpoint method was used to define high and low ARTN concentrations. Cox models (hazard ratios, HR) were used to compare progression-free (PFS, primary endpoint), and overall survival (OS) of pts with high vs low serum ARTN. Results: Pre-operative blood samples were available for 58 pts. Median age was 63 years (range: 25-85 years); 74% were male and 50% were Asian. Etiology of liver disease was hepatitis B (43%) and hepatitis C (22%); 43% of tumors were ≤5cm, and vascular invasion was seen in 62%. A baseline alpha-fetoprotein (AFP) of > 100 mcg/L was observed in 36% pts. Median follow-up was 18.9 months. Median ARTN concentration was 0.322 ng/mL. The optimal ARTN concentration cut-off was 0.206 ng/mL. Median PFS for pts with high ( > 0.206 ng/mL) vs low (≤0.206 ng/mL) ARTN was 15.7 vs 55 months (p = 0.04) respectively. Three year PFS was 34% vs 55%, and three year OS 54% vs 91% for high vs low groups. Univariate analysis found that high ARTN concentration (HR 2.44, p = 0.05) and multifocal tumors were associated with a worse PFS. In a multivariate analysis adjusted for AFP > 100mcg/L, vascular invasion, hepatitis status and multifocal tumors, high ARTN remained a negative prognostic factor for PFS, aHR 3.32 (95% CI: 1.22-9.05, p = 0.02). Conclusions: A high pre-surgery serum ARTN is associated with earlier recurrence in HCC pts undergoing curative resection. ARTN should be further studied in HCC to determine its value as a prognostic marker.
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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 | 0.002 |
| 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".