{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:05:22Z","timestamp":1782846322116,"version":"3.54.5"},"reference-count":45,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Med Inform"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Early diagnosis of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B virus (HBV) is challenging. Models that combine novel biomarkers with clinical features may improve both early diagnosis and risk stratification, but few have been systematically validated.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to develop and validate an extra spindle pole bodies\u2013like 1 (ESPL1)\u2013based model for diagnostic discrimination of HBV-related HCC and longitudinal risk stratification in patients with chronic HBV infection.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Patients with chronic HBV were consecutively recruited from the First Affiliated Hospital of Guangxi Medical University (a single-center, tertiary hospital) between January 2012 and November 2023. Patients were divided into a training set and an independent hold-out testing set. A LASSO logistic regression model was constructed to identify independent predictors and then used to develop a risk score discriminating patients with HBV-related HCC from those with chronic hepatitis B or cirrhosis. Model performance was evaluated using discrimination (C-index), calibration, and decision curve analysis. Internal validation was performed with bootstrap resampling, and independent hold-out validation was conducted with the independent hold-out testing set. Longitudinal follow-up of patients with chronic hepatitis B or cirrhosis was subsequently used to examine cumulative incidence across risk groups, thereby assessing the model\u2019s ability to stratify future HBV-related HCC risk. A web-based calculator was developed to facilitate clinical application.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The study involved a cohort of 621 patients diagnosed with chronic HBV infection, divided into a training set of 373 (60.1%) patients and an independent hold-out testing set of 248 (39.9%) patients. Age (odds ratio [OR] 1.08, 95% CI 1.05\u20101.12), ESPL1 expression (OR 1.01, 95% CI 1.00\u20101.01), and log (alpha-fetoprotein) levels (OR 2.55, 95% CI 1.95\u20103.33) were identified as independent predictors of HBV-related HCC. The model demonstrated excellent diagnostic discrimination, with a C-index of 0.922 in the training set and 0.958 in the independent hold-out testing set, coupled with strong calibration. Decision curve analysis revealed that the model consistently provided a higher net benefit across clinically relevant threshold probabilities. Subgroup analyses further validated the model\u2019s high discriminative power, with C-index values ranging from 0.86 to 0.98, and no significant interactions were detected (all interaction\n P<\/jats:italic>\n values > .10). Furthermore, the model demonstrated superior discriminatory power relative to 5 established HBV-related HCC risk scores, including REACH-B, GAG-HCC, CU-HCC, PAGE-B, mPAGE-B, and alpha-fetoprotein alone, with all pairwise comparisons yielding statistical significance (\n P<\/jats:italic>\n <.001). For prognostic stratification, patients categorized as low risk, medium risk, and high risk had distinct 5-year cumulative HCC incidences of 5.1%, 21.1%, and 31.3%, respectively (\n P<\/jats:italic>\n <.001).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n The ESPL1-based model may serve as both a diagnostic tool for differentiating patients with HCC from those with non-HCC and as a preliminary approach for risk stratification during follow-up. This dual role has the potential to support earlier detection and personalized monitoring. The web-based calculator improves accessibility and may facilitate future clinical integration.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/78354","type":"journal-article","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T19:42:33Z","timestamp":1761162153000},"page":"e78354-e78354","source":"Crossref","is-referenced-by-count":0,"title":["Development and Validation of an Extra Spindle Pole Bodies\u2013like 1\u2013Based Diagnostic and Prognostic Model for Hepatitis B Virus\u2013Related Hepatocellular Carcinoma: Retrospective Cohort 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