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Record W2965163017 · doi:10.1097/jp9.0000000000000027

Liquid biopsies in pancreatic cancer: targeting the portal vein

2019· article· en· W2965163017 on OpenAlexaff
Christopher G. Chapman, Trevor Long, Irving Waxman

Bibliographic record

VenueJournal of Pancreatology · 2019
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsMedicinePancreatic cancerLiquid biopsyMalignancySuperior mesenteric veinRadiologyCancerCirculating tumor cellPortal veinOncologyInternal medicineMetastasis

Abstract

fetched live from OpenAlex

Abstract Pancreatic cancer is a highly lethal malignancy with poor overall survival due to silent progression until primary tumor growth or metastatic dissemination develops clinical symptoms. Even in the minority of patients with early diagnosis and candidacy for curative intent surgery, postoperative recurrence after surgical resection is very frequent. Due to these findings, efforts to identify minimally invasive ways to provide earlier diagnosis and enhanced prognostication are increasingly warranted. Liquid biopsies assessing for tumor derived materials shed into the blood are a promising tool to accomplish this goal; however, in pancreatic cancer, peripheral blood analyses remain dependent on the degree of tumor burden with a prohibitively low yield until the cancer is widely metastatic. To overcome this limitation, increasing literature has emerged evaluating the possibility of portal venous blood as a new, potentially higher yield liquid biopsy target in pancreatic cancer. This review will discuss the current literature and clinical application potential of mesenteric vasculature, or portal venous blood, as liquid biopsies in the diagnosis, prognosis and management of patients with pancreatic cancer.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.339
Teacher spread0.319 · 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 teacher head, not a consensus.

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".

Quick stats

Citations4
Published2019
Admission routes1
Has abstractyes

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