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Record W4393270323 · doi:10.20517/2394-5079.2023.62

The role of percutaneous hepatic perfusion (PHP) in the treatment of cholangiocarcinoma

2024· article· en· W4393270323 on OpenAlexaff
Cornelia L. A. Dewald, Arndt Vogel, Frank Wacker

Bibliographic record

VenueHepatoma Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsToronto General Hospital
FundersDeutsche Forschungsgemeinschaft
KeywordsMedicinePercutaneousPerfusionInternal medicineRadiologyGastroenterologyGeneral surgery

Abstract

fetched live from OpenAlex

This review article evaluates the current literature on the role of percutaneous hepatic perfusion (PHP) as a treatment option in cholangiocarcinoma (CCA). CCA is a rare cancer that is mostly diagnosed at a late stage. Patients with advanced, unresectable disease have limited treatment options. PHP is a locoregional therapy that delivers high doses of chemotherapy directly to the liver while minimizing systemic exposure and toxicity. This review allocates PHP in the therapeutic spectrum of CCA and summarizes the available literature with a focus on the clinical efficacy and safety profile. Results from studies evaluating the efficacy and safety of PHP are promising, with several observational studies demonstrating improvements in progression-free survival and overall survival rates. However, PHP is not without side effects; the most commonly reported adverse events include transient hematotoxicity and hepatotoxicity. PHP has the potential to be a valuable treatment option for patients with unresectable CCA. Nonetheless, further trials are needed to optimize patient selection, treatment regimens, and long-term outcomes.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.048
GPT teacher head0.364
Teacher spread0.315 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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