{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,28]],"date-time":"2026-06-28T07:54:13Z","timestamp":1782633253605,"version":"3.54.5"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:00:00Z","timestamp":1740096000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81960115"],"award-info":[{"award-number":["81960115"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160123"],"award-info":[{"award-number":["82160123"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82260124"],"award-info":[{"award-number":["82260124"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec><jats:title>Objectives<\/jats:title><jats:p>Chronic viral hepatitis B (CHB) is a prevalent liver disease with primary hepatic carcinoma (HCC) as a severe complication. Clinical prediction models have gained attention for predicting HBV-related HCC (HBV-HCC). This study aimed to evaluate the predictive value of existing models for HBV-HCC through meta-analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design<\/jats:title><jats:p>Meta-analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data sources<\/jats:title><jats:p>Embase, PubMed, the Chinese Biomedical Literature Service System, and the Cochrane database were used for searches between 1970 and 2022.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A meta-analysis was conducted to assess original studies on HBV-HCC prediction models. The REACH-B, GAGHCC, and CUHCC models were externally validated in a Guangxi cohort. The C-index and calibration curve evaluated 5 years predictive performance, with subgroup analysis by region and risk bias.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>After screening, 27 research articles were included, covering the GAGHCC, REACH-B, PAGE-B, CU-HCC, CAMD, and mPAGE-B models. The meta-analysis indicated that these models had moderate discrimination in predicting HCC risk in HBV-infected patients, with C-index values from 0.75 to 0.82. The mPAGE-B (0.79, 95% CI: 0.79\u20130.80), GAG-HCC (0.80, 95% CI: 0.78\u20130.82), and CAMD (0.80, 95% CI: 0.78\u20130.81) models demonstrated better discrimination than others (<jats:italic>P<\/jats:italic> &amp;lt; 0.05), but most studies did not report model calibration. Subgroup analysis suggested that ethnicity and research bias might contribute to differences in model discrimination. Sensitivity analysis indicated stable meta-analysis results. The REACH-B, GAGHCC, CUHCC, PAGE-B, and mPAGE-B models had average predictive performance in Guangxi, with medium to low 3 and 5 years HCC risk prediction discrimination.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Existing models have predictive value for HBV-infected patients but show geographical limitations and reduced effectiveness in Guangxi.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmed.2025.1529201","type":"journal-article","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T05:19:13Z","timestamp":1740115153000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Evaluating the predictive value of clinical models for HBV-related hepatocellular carcinoma: A 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