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Record W4381104026 · doi:10.7759/cureus.40592

A Comparison of the Outcomes of Transarterial Chemoembolization and Transarterial Radioembolization in the Management of Neuroendocrine Liver Metastases in Adults: A Systematic Review

2023· review· en· W4381104026 on OpenAlexaboutno aff
Nishok Victory Srinivasan, Sathish Venugopal

Bibliographic record

VenueCureus · 2023
Typereview
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialObservational studyMeta-analysisRadiologyInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this article is to review the existing English scientific literature and determine the superior modality between transarterial chemoembolization (TACE) and radioembolization (TARE) in the treatment of neuroendocrine liver metastases (NELMs). To that end, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to search PubMed, the Cochrane Library, and Google Scholar. We identified 14 observational studies and no randomized controlled trials (RCTs) investigating the use of TACE or TARE to treat NELM. We used the Newcastle-Ottawa Scale to assess the risk of bias in these studies. We concluded that TACE and TARE appeared to have similar outcomes when comparing overall survival, progression-free survival, radiological response, symptomatic response, and the incidence of severe adverse events. Further large-scale RCTs are needed to identify the superior modality conclusively. We also identified several unique prognostic factors for overall survival, such as the neutrophil-lymphocyte ratio, volumetric multiparametric magnetic resonance imaging, serum albumin, alkaline phosphatase, and pancreastatin.

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)0.008
metaresearch head score (Gemma)0.029
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: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.011
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.408
Teacher spread0.338 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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Same venueCureusSame topicNeuroendocrine Tumor Research AdvancesFrench-language works237,207