Background/Aims A large percentage of patients undergoing esophagogastroduodenoscopy (EGD) screening do not have esophageal varices (EV) or have only small EV. We evaluated a large, international, multicenter cohort to develop a novel score, termed FIB-4plus, by combining the fibrosis-4 (FIB-4) score, liver stiffness measurement (LSM), and spleen stiffness measurement (SSM) to identify high-risk EV (HRV) in compensated cirrhosis.
Methods This international cohort study involved patients with compensated cirrhosis from 17 Chinese hospitals and one Croatian institution (NCT04546360). Two-dimensional shear wave elastography-derived LSM and SSM values, and components of the FIB-4 score (i.e., age, aspartate aminotransferase, alanine aminotransferase, and platelet count [PLT]) were combined using machine learning algorithms (logistic regression [LR] and extreme gradient boosting [XGBoost]) to develop the LR-FIB-4plus and XGBoost-FIB-4plus models, respectively. Shapley Additive exPlanations method was used to interpret the model predictions.
Results We analyzed data from 502 patients with compensated cirrhosis who underwent EGD screening. The XGBoost-FIB-4plus score demonstrated superior predictive performance for HRV, with an area under the receiver operating characteristic curve (AUROC) of 0.927 (95% confidence interval [CI] 0.897–0.957) in the training cohort (n=268), and 0.919 (95% CI 0.843–0.995) and 0.902 (95% CI 0.820–0.984) in the first (n=118) and second (n=82) external validation cohorts, respectively. Additionally, the XGBoost-FIB-4plus score exhibited high AUROC values for predicting EV across all cohorts. The FIB-4plus score outperformed the individual parameters (LSM, SSM, PLT, and FIB-4).
Conclusions The FIB-4plus score effectively predicted EV and HRV in patients with compensated cirrhosis, providing clinicians with a valuable tool for optimizing patient management and outcomes.
Citations
Citations to this article as recorded by
Relative change rate of liver stiffness measurements predicts the risk of liver decompensation in compensated advanced chronic liver disease Yanqiu Li, Zihang Qiao, Jinze Li, Bingbing Zhu, Yu Lu, Ying Feng, Xianbo Wang Clinical and Experimental Medicine.2025;[Epub] CrossRef
The Evolution of Non-Invasive Strategies in Cirrhosis Management—From Screening to Precision Monitoring：Editorial on ‘FIB-4plus Score: A novel machine learning-based tool for screening high-risk varices in compensated cirrhosis (CHESS2004): An internation Haiyu Wang, Jinjun Chen Clinical and Molecular Hepatology.2025;[Epub] CrossRef
Artificial Intelligence Applications in the Diagnosis and Management of Cirrhosis and Portal Hypertension: A Narrative Review Amrit Khooblall, Satish E. Viswanath, Layth Khawaja, Sameer Gadani Techniques in Vascular and Interventional Radiology.2025; : 101078. CrossRef
Backgrounds/Aims Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model.
Methods Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort.
Results In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM).
Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.
Citations
Citations to this article as recorded by
Endoscopic variceal ligation combined with carvedilol versus endoscopic variceal ligation combined with propranolol for the treatment of oesophageal variceal bleeding in cirrhosis: study protocol for a multicentre, randomised controlled trial Yiling Li, Li Du, Shuairan Zhang, Chuan Liu, Chao Ma, Xiaochao Liu, Huanhai Xu, Zhixu Fan, Shengjuan Hu, Jing Wang, Lichun Shao, Lijun Peng, Huiling Xiang, Xuan Liang, Wenhui Zhang, Hongyun Zhao, Pengyuan He, Jingyi Xu, Qianlong Li, Ling Yang, Yunhai Wu, BMJ Open.2025; 15(4): e093866. CrossRef
Relative change rate of liver stiffness measurements predicts the risk of liver decompensation in compensated advanced chronic liver disease Yanqiu Li, Zihang Qiao, Jinze Li, Bingbing Zhu, Yu Lu, Ying Feng, Xianbo Wang Clinical and Experimental Medicine.2025;[Epub] CrossRef
Revolutionising portal hypertension diagnosis: the rise of non-invasive techniques in liver cirrhosis Bocheng Gao, Yumeng Lin, Huimin Zhang, Yulin Li, Shuhua Gou, Peiling Ma, Xueni Zhao, Yue Zhou, Qian Chen, Lan Yuan, Zhongyu Han, Chang Yu Frontiers in Medicine.2025;[Epub] CrossRef
Editorial: Non‐selective beta‐blockers: A lifesaving shield for critically ill patients with acute decompensation of cirrhosis? Ling Yang, Chuan Liu, Jimmy Che‐To Lai, Xiaolong Qi Alimentary Pharmacology & Therapeutics.2024; 60(7): 965. CrossRef
First
Prev
