Evidence map›Paper›PMID 41378868›Full record

ArticleBiomarkers in medicine2025

Development of a novel diagnostic model integrating microRNAs and GALAD for HBV-related hepatocellular carcinoma.

Yihui Yang, Anli Jin, Yan Zhou, Wenhao Wu, Chunyan Zhang, Baishen Pan, Beili Wang, Yunfan Sun, Wei Guo

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Article in Biomarkers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Yihui YangDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Anli JinDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Yan ZhouDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Wenhao WuDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Chunyan ZhangDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Baishen PanDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Beili WangDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Yunfan SunDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Wei GuoDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsAs primary hepatocellular carcinoma (HCC) is a prevalent digestive tract malignancy, identifying novel biomarkers for early diagnosis and prognosis is crucial. This study combined specific miRNAs with the GALAD model to create a new diagnostic model for hepatitis B virus (HBV)-related HCC. PATIENTS &

methodsFrom 2020 to 2022, 884 patients from Zhongshan Hospital were enrolled, including 430 HBV-related HCC, 275 HBV-related chronic liver disease (CLD), and 179 healthy donors (HD). Stepwise regression selected features, and multivariable logistic regression built the GALADM model. A nomogram integrating age, gender, serum markers, and a score derived from seven plasma cell-free microRNAs (miRNA7) was developed.

resultsMiRNA7 value was higher in HCC patients and rose with disease progression. The GALADM model showed superior diagnostic performance, with AUCs of 0.87, 0.96, and 0.90 when distinguishing HCC from CLD, HD, and CLD+HD, outperforming the GALAD model and single markers. It also excelled in diagnosing early-stage and Alpha-fetoprotein (AFP)-negative HCC. The nomogram had an AUC of 0.977 and proved clinically useful.

conclusionThe GALADM model, combining miRNA7 with the GALAD model, surpasses the original GALAD model, enabling early-stage and AFP-negative HCC diagnosis.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularHepatitis BHepatitis B virusLiver NeoplasmsMicroRNAsAdultalpha-FetoproteinsFemaleHumansMaleMiddle AgedNomogramsalpha-FetoproteinsBiomarkers, TumorMicroRNAsBiomarkerdiagnostic modelGALADMhepatocellular carcinomamicroRNAs

Identifiers

PMID41378868
PMCPMC12758346

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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.