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Transarterial Chemoembolization as a Bridge to Liver Transplantation for Hepatocellular Carcinoma: An Evidence-Based Analysis

2006· review· en· W2064897165 on OpenAlexaff
Mickaël Lesurtel, Beat Müllhaupt, Bernhard C. Pestalozzi, T. Pfammatter, Pierre‐Alain Clavien

Bibliographic record

VenueAmerican Journal of Transplantation · 2006
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsMedicineHepatocellular carcinomaLiver transplantationGrading (engineering)Randomized controlled trialInternal medicineMilan criteriaMEDLINETransplantationOncologySurgery

Abstract

fetched live from OpenAlex

The aim of this review was to assess the impact of transarterial chemoembolization (TACE) as a neoadjuvant therapy prior to orthotopic liver transplantation (OLT) for hepatocellular carcinoma (HCC). An electronic search on the Medline database (1990-2005) was used to identify relevant articles. The studies were reviewed and ranked according to their quality of evidence using the grading system proposed by the Oxford Centre for Evidence-based Medicine. As a bridge to OLT, pretransplant TACE does not improve long-term survival (grade C). There is currently no convincing evidence that TACE allows to expand the current selection criteria for OLT, nor that TACE decreases dropout rates on the waiting list (grade C). However, TACE does not increase the risk for postoperative complications (grade C). There is insufficient evidence that TACE offers any benefit when used prior to OLT, neither for early nor for advanced HCC. Well-designed randomized controlled trials are needed to define the role of TACE in OLT patients.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.098
GPT teacher head0.333
Teacher spread0.235 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations174
Published2006
Admission routes1
Has abstractno

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