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DiabetesLiver score: A non-invasive algorithm for advanced liver fibrosis and liver-related outcomes in type 2 diabetes mellitus population

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资源类型：
Pubmed体系：
作者：
Liu Chuan[1,2] * ; Shen Jie[3] * ; Li Jie[4] * ; Li Zhihui[5] * ; Zheng Ming-Hua[6,7] * ; Bian Hua[8] * ; Zhou Xiqiao[9] * ; Ni Wenjing[4,10] * ; Meng Zhongji[11] * ; Lv Jiaojian[12] * ; Tang Yijun[13] ; Liang Xuan[14] ; Li Min[15] ; Zhou Taolong[16] ; Wan Heng[3] ; Chen Yuping[1,2] ; Qi Yuxia[17] ; Ge Yuli[12] ; Wang Yan[14] ; Liu Wen-Yue[18] ; Huang Mingxing[16] ; Liu Shanghao[1,2] ; Wang Xiaomei[14] ; Xia Mingfeng[8,19] ; Li Xuefeng[15] ; Wang Yuehua[20] ; Li Xinjie[21] ; Hu Xiaoxiong[22] ; Wu Yan[23] ; Ying Huimin[24] ; He Jing[25] ; Wang Fengmei[26] ; Yan Wei[27] ; Wu Huili[28] ; Zhang Qingge[29] ; Jiang Weimin[30] ; Huang Yan[31] ; Zhang Yudong[32] ; He Hongliang[33] ; Wu Xiaofeng[34] ; Zhang Yuwei[35] ; Li Ling[36] ; Cheuk-Fung Yip Terry[37] ; Teng Gao-Jun[2,38] ; Qi Xiaolong[1,2] ;
机构： [1]Liver Disease Center of Integrated Traditional Chinese and Western Medicine, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China [2]Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, State Key Laboratory of Digital Medical Engineering, Nanjing, China [3]Department of Endocrinology and Metabolism, Shunde Hospital, Southern Medical University (The First People’s Hospital of Shunde), Foshan, China [4]Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China [5]Vanke School of Public Health, Tsinghua University, Beijing, China [6]MAFLD Research Center, Department of Hepatology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China [7]Key Laboratory of Diagnosis and Treatment for the Development of Chronic Liver Disease in Zhejiang Province, Wenzhou, China [8]Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China [9]Department of Endocrinology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China [10]Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China [11]Department of Infectious Diseases, Hubei Provincial Clinical Research Center for Precise Diagnosis and Treatment of Liver Cancer, Taihe Hospital, Hubei University of Medicine, Shiyan, China [12]Department of Infectious Diseases, Lishui People’s Hospital, Lishui, China [13]Department of Pulmonary and Critical Care Medicine, Hubei Provincial Clinical Research Center for Precision Diagnosis and Treatment of Liver Cancer, Taihe Hospital, Hubei University of Medicine, Shiyan, China [14]The Sixth People’s Hospital of Shenyang, Shenyang, China [15]Department of Endocrinology, Taihe Hospital, Hubei University of Medicine, Shiyan, China [16]Center of Co-management of Diabetes-Liver Diseases, Zhuhai Third People’s Hospital, Zhuhai, China [17]Department of Internal Medicine, Qingdao Public Health Clinical Center, Qingdao, China [18]Department of Endocrinology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China [19]Fudan Institute for Metabolic Diseases, Fudan University, Shanghai, China [20]Jinhua People’s Hospital, Jinhua, China [21]Department of Endocrinology, Bozhou People’s Hospital, Bozhou, China [22]Department of Infectious Diseases, Yichun People’s Hospital, Yichun, China [23]Suining Central Hospital, Suining, China [24]Department of Endocrinology, Xixi Hospital, Hangzhou, China [25]The Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China [26]Gansu Wuwei Cancer Hospital, Wuwei, China [27]Linfen Central Hospital, Linfen, China [28]Department of Gastroenterology, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China [29]Xingtai People’s Hospital, Xingtai, China [30]Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China [31]Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China [32]School of Computer Science and Engineering, Southeast University, Nanjing, China [33]State Key Laboratory of Digital Medical Engineering, Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China [34]State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China [35]Department of Endocrinology & Metabolism, Center for Diabetes and Metabolism Research, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China [36]Department of Endocrinology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China [37]Medical Data Analytic Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China [38]Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
出处：
DOI： 10.1016/j.medj.2025.100700
ISSN：

摘要：
This study aimed to develop and validate a non-invasive model for screening advanced liver fibrosis and predicting liver-related outcomes in patients with type 2 diabetes mellitus (T2DM).This study included patients with T2DM from five tertiary hospitals for the development and internal validation of a non-invasive model. Advanced liver fibrosis was defined as a liver stiffness measurement ≥12 kPa. An external validation cohort was obtained from the National Health and Nutrition Examination Survey (NHANES), and the model's predictive performance for hepatocellular carcinoma (HCC) and liver-related mortality was assessed in the UK Biobank.In total, 28,197 patients with T2DM were enrolled. In the derivation cohort (n = 1,129), waist circumference, alanine aminotransferase, aspartate aminotransferase, platelet count, and albumin were identified as independent risk factors for advanced fibrosis and were fit to develop the "DiabetesLiver score." The area under the curve (AUC) was 0.835 (95% confidence interval [CI]: 0.781-0.890), significantly higher than the AUCs of non-invasive tests (all p < 0.01). It maintained high AUCs of 0.870 and 0.823 in the internal validation (n = 1,000), and NHANES cross-sectional (n = 1,432) cohorts, respectively. A dual cutoff of 2.39 and 3.99 with sensitivity ≥90% and specificity ≥90%, respectively, was used to classify patients into low-, middle-, and high-risk groups. In the UK Biobank cohort (n = 24,636), the high-risk group had an elevated risk of liver-related outcomes.The DiabetesLiver score demonstrated good performance in identifying advanced liver fibrosis and the development of liver-related events in the T2DM population.National Natural Science Foundation.Copyright © 2025 Elsevier Inc. All rights reserved.

基金：
National Natural Science Foundation.
语种：
外文
PubmedID：
中科院(CAS)分区：
出版当年[2025]版：
大类 | 1 区 医学
小类 | 1 区 医学：研究与实验
最新[2025]版：
大类 | 1 区 医学
小类 | 1 区 医学：研究与实验
第一作者：
第一作者机构： [1]Liver Disease Center of Integrated Traditional Chinese and Western Medicine, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China [2]Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, State Key Laboratory of Digital Medical Engineering, Nanjing, China
共同第一作者：
通讯作者：
通讯机构： [1]Liver Disease Center of Integrated Traditional Chinese and Western Medicine, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China [2]Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, State Key Laboratory of Digital Medical Engineering, Nanjing, China [38]Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
推荐引用方式(GB/T 7714)：
Liu Chuan,Shen Jie,Li Jie,et al.DiabetesLiver score: A non-invasive algorithm for advanced liver fibrosis and liver-related outcomes in type 2 diabetes mellitus population[J].Med (New York, N.Y.).2025,100700.doi:10.1016/j.medj.2025.100700.
APA：
Liu Chuan,Shen Jie,Li Jie,Li Zhihui,Zheng Ming-Hua...&Qi Xiaolong.(2025).DiabetesLiver score: A non-invasive algorithm for advanced liver fibrosis and liver-related outcomes in type 2 diabetes mellitus population.Med (New York, N.Y.),,
MLA：
Liu Chuan,et al."DiabetesLiver score: A non-invasive algorithm for advanced liver fibrosis and liver-related outcomes in type 2 diabetes mellitus population".Med (New York, N.Y.) .(2025):100700

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