What question did this study set out to answer?

This research aims to develop a model to accurately exclude high-risk varices in patients with HBV-related cirrhosis.

February 27, 2026Open Access

A novel dual elastography-based model for screening high-risk varices in hepatitis B virus-related cirrhosis

Key Points

This research aims to develop a model to accurately exclude high-risk varices in patients with HBV-related cirrhosis.
Recruitment of consecutive patients with HBV-related cirrhosis from five centers.
Patients underwent dual elastography and an EGD within one week.
Machine learning techniques were employed to identify predictive variables from a training cohort of four centers.
The model was externally validated using an independent cohort from the fifth center.
The DELU model achieved AUROCs of 0.822 in training and 0.779 in validation cohorts.
DELU outperformed RESIST and B6C in predictive capability for high-risk varices.
The model demonstrated high rates of spared endoscopic procedures (20.7% training; 11.1% validation).
Performance remained robust across different patient subgroups, including various Child-Pugh classifications.

Abstract

Background and objective Variceal bleeding carries high mortality and recurrence rates, underscoring the urgent need for effective non-invasive tests (NITs) to assess the severity of esophageal varices (EVs) and predict bleeding risk. This study aimed to develop and validate a robust model for safely excluding high-risk varices (HRVs) in patients with hepatitis B virus (HBV)-related cirrhosis and to compare its diagnostic performance and clinical utility with established NITs. Methods Consecutive patients with HBV-related cirrhosis were prospectively recruited from five centers and underwent dual elastography (dual-elasto) within 1 week of esophagogastroduodenoscopy (EGD). A training cohort from four centers was used to identify predictive variables for HRVs, which were analyzed using machine learning to develop the most reliable model. The final model was externally validated in an independent cohort from the fifth center. Diagnostic efficacy and clinical utility were compared across multiple NITs, including the Baveno VI criteria (B6C), expanded Baveno VI criteria (EB6C), platelet–spleen ratio (PSR), and RESIST-HCV criteria (RESIST). Results Among 703 screened patients, 328 were enrolled (training cohort n = 184; validation cohort n = 144). Using logistic regression, we developed the DELU model incorporating six variables: platelet count (PLT), alanine aminotransferase (ALT), ascites, portal vein thrombosis (PVT), inverse difference moment (IDM), and liver stiffness (liver Vs). DELU achieved areas under the receiver operating characteristic curve (AUROCs) of 0.822 (training) and 0.779 (validation), outperforming RESIST (0.600 and 0.626) and B6C (0.569 and 0.575). EB6C and PSR were excluded because they exceeded the 5% missed-HRV threshold. DELU demonstrated the highest spared-EGD rates (20.7% training; 11.1% validation) and maintained robust performance across subgroups, including Child-Pugh B/C (AUROC 80.3%), Child-Pugh A (79.7%), antiviral therapy (ART)-treated (82.5%), and virologically suppressed patients (84.6%). Performance was not influenced by hepatocellular carcinoma (HCC) status, sex, or body mass index (BMI). Conclusion DELU is a reliable and safe non-invasive tool for excluding HRVs in HBV-related cirrhosis, providing superior diagnostic accuracy and significant endoscopy-sparing potential across diverse clinical settings. RESIST may serve as a safe alternative when elastography is unavailable. Clinical trial registration ClinicalTrials.gov, identifier NCT04640350.

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