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Preoperative serum artemin (ARTN) as a predictive biomarker of recurrence following curative resection for hepatocellular carcinoma (HCC).

2020· article· en· W3004419783 on OpenAlexaff
Sophie Feng, Hao‐Wen Sim, Roxana Bucur, Reenika Aggarwal, Phillipe Abreu, Monali Ray, Michael Herman, Dangxiao Cheng, Zhuo Chen, Wenjiang Zhang, Paul D. Greig, Alice C. Wei, Carol-Anne Moulton, I. McGilvray, Sean P. Cleary, Steven Gallinger, Gonzalo Sapisochín, Jennifer J. Knox, Geoffrey Liu, Eric Xueyu Chen

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsUniversity of TorontoToronto General HospitalUniversity Health NetworkPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineHepatocellular carcinomaInternal medicineHazard ratioBiomarkerOncologyGastroenterologyConfidence interval

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.143
GPT teacher head0.468
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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