Evidence map›Paper›PMID 40287734›Full record

ReviewWorld journal of surgical oncology2025

Predictive factors and prognostic models for Hepatic arterial infusion chemotherapy in Hepatocellular carcinoma: a comprehensive review.

Xing Lv, Peng-Bo Zhang, Er-Lei Zhang, S Yang

Abstract readReview
In one paragraph

Review in World journal of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xing LvHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Peng-Bo ZhangHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Er-Lei ZhangHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
S YangDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China. yangshuhong0108@tjh.tjmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a prevalent and lethal cancer, often diagnosed at advanced stages where traditional treatments such as surgical resection, liver transplantation, and locoregional therapies provide limited benefits. Hepatic arterial infusion chemotherapy (HAIC) has emerged as a promising treatment modality for advanced HCC, enhancing anti-tumor efficacy through targeted drug delivery while minimizing systemic side effects. However, the heterogeneous nature of HCC leads to variable responses to HAIC, highlighting the necessity for reliable predictive indicators to tailor personalized treatment strategies. This review explores the factors influencing HAIC success, including patient demographics, tumor characteristics, biomarkers, genomic profiles, and advanced imaging techniques such as radiomics and deep learning models. Additionally, the synergistic potential of HAIC combined with immunotherapy and molecular targeted therapies is examined, demonstrating improved survival outcomes. Prognostic scoring systems and nomograms that integrate clinical, molecular, and imaging data are discussed as superior tools for individualized prognostication compared to traditional staging systems. Understanding these predictors is essential for optimizing HAIC efficacy and enhancing survival and quality of life for patients with advanced HCC. Future research directions include large-scale prospective studies, integration of multi-omics data, and advancements in artificial intelligence to refine predictive models and further personalize treatment approaches.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsCarcinoma, HepatocellularLiver NeoplasmsBiomarkers, TumorHepatic ArteryHumansInfusions, Intra-ArterialNomogramsPrognosisBiomarkers, Tumor

Identifiers

PMID40287734
PMCPMC12034129

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.