Evidence map›Paper›PMID 41508340›Full record

ReviewClinical and molecular hepatology2026

Hepatocellular carcinoma surveillance: a health economic evaluation.

Qi-Feng Chen, Xiong-Ying Jiang, Song Chen, Jiongliang Wang, Ming Zhao

Abstract readReview
In one paragraph

Review in Clinical and molecular hepatology, 2026. 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. Toward Precise Risk Stratification after the Functional Cure of Chronic Hepatitis B.The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi · 2026
    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

5 authors.

Qi-Feng ChenDepartment of Minimally Invasive Interventional Therapy, Liver Cancer Study and Service Group, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Xiong-Ying JiangDepartment of Interventional Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Song ChenDepartment of Interventional Radiology, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Jiongliang WangDepartment of Minimally Invasive Interventional Therapy, Liver Cancer Study and Service Group, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Ming ZhaoDepartment of Minimally Invasive Interventional Therapy, Liver Cancer Study and Service Group, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.

Funding

GuangDong Basic and Applied Basic Research Foundation 2025A1515011330National Natural Science Foundation of China 82372061National Natural Science Foundation of China 82402403
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) imposes a major health and economic burden worldwide, with disproportionate effects in low- and middle-income countries (LMICs). Surveillance in high-risk populations, typically using semiannual ultrasound and alpha-fetoprotein testing, has been shown to be cost-effective by enabling earlier detection and improving survival. Yet, its overall value is reduced by poor adherence and the limited sensitivity of ultrasound, particularly in patients with metabolic-associated steatotic liver disease. Emerging approaches-including abbreviated magnetic resonance imaging, multi-biomarker models (e.g., gender, age, AFP, AFP-L3, and DCP), and liquid biopsy assays such as methylated DNA markers-demonstrate greater diagnostic accuracy and potential economic advantages compared with conventional methods. Integration of artificial intelligence into imaging may further enhance efficiency and reduce downstream costs. Moving toward precision surveillance, guided by individualized risk stratification that incorporates etiology, fibrosis stage, and molecular profiles, can optimize allocation of resources and maximize cost-effectiveness at the population level. Interventions to improve adherence, including mailed outreach and behavioral economic incentives, have shown both clinical benefit and cost savings, underscoring the role of implementation science. Because socioeconomic disparities influence both access and outcomes, economic models must explicitly address equity to achieve sustainable impact. Future research should prioritize prospective trials that evaluate not only clinical performance but also the real-world cost-effectiveness of novel technologies and stratified surveillance strategies. For LMICs, adapting proven models into affordable, context-appropriate programs is essential. By combining prevention, precision risk assessment, innovative technologies, and equitable implementation, HCC surveillance can deliver both clinical and economic value, reducing the global burden of disease.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkers, TumorCost-Benefit AnalysisCost-Effectiveness AnalysisHumansMagnetic Resonance ImagingUltrasonographyBiomarkers, TumorAbbreviated magnetic resonance imagingCost-effectivenessHealth economicsLiver cancerSurveillance

Identifiers

PMID41508340
PMCPMC13129772

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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 Socratic graph.