Evidence map›Paper›PMID 39159949›Full record

ReviewClinical and molecular hepatology2025

Criteria and prognostic models for patients with hepatocellular carcinoma undergoing liver transplantation.

Meng Sha, Jun Wang, Jie Cao, Zhi-Hui Zou, Xiao-Ye Qu, Zhi-Feng Xi, Chuan Shen, Ying Tong, Jian-Jun Zhang, Seogsong Jeong and 1 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinical and molecular hepatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

11 authors.

Meng ShaDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Jun WangState Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jie CaoDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Zhi-Hui ZouDepartment of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Naval Military Medical University, Shanghai, China.
Xiao-Ye QuDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Zhi-Feng XiDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Chuan ShenDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Ying TongDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Jian-Jun ZhangDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Seogsong JeongDepartment of Biomedical Informatics, Korea University College of Medicine, Seoul, Korea.
Qiang XiaDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Funding

Chenguang Program of Shanghai Education Development FoundationCultivation Foundation of Renji Hospital RJPY-LX-011National Natural Science Foundation of China 81902379Shanghai Municipal Education Commission 21CGA20
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsLiver TransplantationHumansPatient SelectionPrognosisHepatocellular carcinomaLiver transplantationNomogramStandards

Identifiers

PMID39159949
PMCPMC11925443

What OpenQuestion holds

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Registered trials

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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.