Evidence map›Paper›PMID 42032544›Full record

ArticleBMC infectious diseases2026

Development and validation of a modified PAGE-B score based nomogram for predicting hepatocellular carcinoma in antiviral-treated chronic hepatitis B patients with metabolic dysfunction.

Qian Wei, Yinglun Li, Ze Chen, Jing Liu, Xue Jiao, Yibing Zhou, Yuqiang Mi, Ping Li

Abstract readValidation Study
In one paragraph

Article in BMC infectious diseases, 2026. 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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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Qian Wei *The Second People's Hospital Affiliated to Tianjin Medical University Tianjin, Tianjin, China.
Yinglun Li *The Second People's Hospital Affiliated to Tianjin Medical University Tianjin, Tianjin, China.
Ze ChenThe Second People's Hospital Affiliated to Tianjin Medical University Tianjin, Tianjin, China.
Jing LiuThe Second People's Hospital Affiliated to Tianjin Medical University Tianjin, Tianjin, China.
Xue JiaoThe Second People's Hospital Affiliated to Tianjin Medical University Tianjin, Tianjin, China.
Yibing ZhouDepartment of Scientifc Research, Central Laboratory, Changshu Hospital Afliated to Soochow University, Changshu No.1 People's Hospital, Changshu, 215500, China.
Yuqiang MiTianjin Institute of Hepatology, Tianjin Second People's Hospital Tianjin, Tianjin, 300192, PR China.
Ping LiTianjin Institute of Hepatology, Tianjin Second People's Hospital Tianjin, Tianjin, 300192, PR China. tjlplxg@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to construct and validate a nomogram to predict the long-term incidence of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) and metabolic dysfunction (MD) receiving antiviral therapy.

methods809 individuals with hepatitis B combined with metabolic dysfunction who received antiviral therapy between 2009 and 2023 were randomly assigned to the training and validation cohorts in a 6:4 ratio using simple randomization performed with the sample function in R software (version 4.3.2). Independent risk factors for HCC were identified by Cox regression analysis, and a nomogram was subsequently constructed. The model’s performance was evaluated using calibration curves, decision curve analysis (DCA), and the area under the receiver operating characteristic curve (AUC).

resultsIndependent predictors of HCC development identified by multivariate Cox regression included lymphocyte count, the Triglyceride-Glucose index, and the modified PAGE-B score. These were incorporated into a nomogram with a total score range of 0 to 200 for risk prediction. The nomogram yielded a 3-year AUC of 0.828, numerically higher than established scores; however, DeLong tests confirmed no statistically significant superiority. Using the nomogram for risk stratification, the 5-year cumulative HCC incidence in the derivation cohort was 2.5% in the low-risk, 9.7% in the medium-risk, and 20.0% in the high-risk group. The validation cohort showed corresponding incidence rates of 0.8%, 12.7%, and 18.5%.

conclusionOur nomogram demonstrated favorable discriminative ability and calibration accuracy for predicting HCC risk among antiviral-treated patients with CHB and MD. Patients stratified into the high-risk group (scores > 151) could be prioritized for intensified surveillance, highlighting the model’s utility in risk-stratified clinical management. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Antiviral AgentsCarcinoma, HepatocellularHepatitis B, ChronicLiver NeoplasmsNomogramsAdultFemaleHumansIncidenceMaleMiddle AgedRisk FactorsROC CurveAntiviral AgentsAntiviral therapyChronic hepatitis B (CHB)Hepatocellular carcinoma (HCC)Metabolic dysfunction(MD)Risk stratification nomogramSurveillance

Identifiers

PMID42032544
PMCPMC13255432

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.