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一种预测慢性乙型肝炎急性肝衰竭移植后1年死亡率的新型预后模型的开发与验证:一项全国性、多中心队列研究。

Development and validation of a novel prognostic model to predict 1-year post-transplant mortality for acute-on-chronic hepatitis B liver failure: a nationwide, multicentre, cohort study.

作者信息

Zhuang Li, Lin Yimou, Jia Yu, Fang Jun, Zheng Yujian, Fang Taishi, Ong Meiching, Mu Aibo, Zhu Jiaxing, Wang Mengchao, Zhao Dong, Deng Feiwen, Lei Qiucheng, Xu Leibo, Yang Zuozhong, Sun Qiang, Qu Wei, Xu Chenwei, Zhu Zhijun, Li Chuanjiang, Jiang Hanyu, Liu Jimin, He Xiaoshun, Zheng Shusen, Guo Zhiyong, Ling Qi

机构信息

Department of Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China.

Department of Hepatobiliary and Pancreatic Surgery, Shulan (Hangzhou) Hospital, Hangzhou 310000, China.

出版信息

EClinicalMedicine. 2025 Jul 17;86:103365. doi: 10.1016/j.eclinm.2025.103365. eCollection 2025 Aug.

DOI:10.1016/j.eclinm.2025.103365
PMID:40727008
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12303012/
Abstract

BACKGROUND

Liver transplantation (LT) provides a potential cure for hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). We aimed to develop and externally validate a prognostic model to predict 1-year post-LT mortality in patients with HBV-ACLF.

METHODS

This retrospective, nationwide, observational cohort study was conducted at ten high-volume LT centres in China. 4378 adult patients who underwent primary LT between January 2015 and December 2021 were screened, and those with HBV-ACLF according to the COSSH-ACLF criteria (separated into three ACLF grades based on the number of organ failures) were included. The HBV-ACLF LT (HALT) model was developed in the derivation cohort and validated in the external testing cohort. The derivation cohort were derived from two LT centres in one province (Zhejiang). The external testing cohort were derived from eight LT centres in two provinces. For model development, univariable Cox regression analysis was used to identify risk factors associated with 1-year post-LT mortality. Variables with univariable < 0.05 were entered into the least absolute shrinkage and selection operator (Lasso) analysis for further feature selection. 10-fold cross validation was used to choose the optimal lambda (penalty for the number of features) of the Lasso model. Multivariable Cox regression was applied to construct the HALT model based on the risk factors selected by Lasso analysis. Primary outcome was survival rate at 1-year after LT. Secondary outcomes were short-term (28- and 90-day) and long-term survival after LT (3- and 5-year). Model performance was compared with eight other models (COSSH-ACLF II, COSSH-ACLF, CLIF-C ACLF, AARC, MELD, MELD-Na, SALT-M and TAM scores), using receiver operating characteristic curve and C-index values. A nomogram was developed to analyse the probability of the primary outcome in different graft-recipient combinations based on recipient factors (age, number of organ failures [OF], lactate) and graft factors (donation after circulatory death [DCD] and cold ischaemia time [CIT]).

FINDINGS

Between Jan 1, 2015, and Dec 1, 2021, 668 patients were included (derivation cohort, n = 418; external testing cohort, n = 250), with survival rates of 88.0%, 81.1%, 77.5%, 75.6% and 72.1% at 28-day, 90-day, 1-year, 3-year and 5-year post-LT, respectively. Three recipient's factors (age, number of OF and arterial lactate concentration) as well as two graft's parameters (DCD and CIT) were independently associated with 1-year post-LT mortality in the derivation cohort (all < 0.05). The HALT model was established accordingly, showing better discriminative performance (C-index, 0.791) than eight current models in the external testing cohort (C-index, 0.529-0.627; all < 0.001). If the sickest patients (age >55 years, OFs ≥3 and lactate ≥2.5 mmol/L) received high-risk grafts (DCD and CIT >10 h), the estimated 1-year post-LT mortality was 85.6%.

INTERPRETATION

The HALT model showed superior predictive ability over eight current models and may help for LT candidate selection and optimal organ allocation. Though the findings need to be verified in prospective studies and among different patient populations.

FUNDING

This work was supported by grants from the National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province, and the Research Project of Jinan Microecological Biomedicine Shandong Laboratory.

摘要

背景

肝移植(LT)为乙型肝炎病毒相关慢加急性肝衰竭(HBV-ACLF)提供了潜在的治愈方法。我们旨在开发并外部验证一个预测模型,以预测HBV-ACLF患者肝移植术后1年的死亡率。

方法

本回顾性、全国性、观察性队列研究在中国的10个高容量肝移植中心进行。筛选了2015年1月至2021年12月期间接受初次肝移植的4378例成年患者,并纳入了根据COSSH-ACLF标准诊断为HBV-ACLF的患者(根据器官衰竭数量分为三个ACLF等级)。HBV-ACLF肝移植(HALT)模型在推导队列中开发,并在外部测试队列中进行验证。推导队列来自一个省份(浙江)的两个肝移植中心。外部测试队列来自两个省份的八个肝移植中心。对于模型开发,采用单变量Cox回归分析来识别与肝移植术后1年死亡率相关的危险因素。单变量P<0.05的变量进入最小绝对收缩和选择算子(Lasso)分析进行进一步的特征选择。采用10折交叉验证来选择Lasso模型的最佳λ(特征数量的惩罚项)。基于Lasso分析选择的危险因素,应用多变量Cox回归构建HALT模型。主要结局是肝移植术后1年的生存率。次要结局是肝移植术后短期(28天和90天)和长期(3年和5年)生存率。使用受试者工作特征曲线和C指数值,将模型性能与其他八个模型(COSSH-ACLF II、COSSH-ACLF、CLIF-C ACLF、AARC、MELD、MELD-Na、SALT-M和TAM评分)进行比较。开发了一个列线图,以根据受者因素(年龄、器官衰竭数量[OF]、乳酸)和移植物因素(循环死亡后捐赠[DCD]和冷缺血时间[CIT])分析不同移植物-受者组合中主要结局的概率。

结果

2015年1月1日至2021年12月1日期间,共纳入668例患者(推导队列,n = 418;外部测试队列,n = 250),肝移植术后28天、90天、1年、3年和5年的生存率分别为88.0%、81.1%、77.5%、75.6%和72.1%。在推导队列中,三个受者因素(年龄、OF数量和动脉血乳酸浓度)以及两个移植物参数(DCD和CIT)与肝移植术后1年死亡率独立相关(均P<0.05)。据此建立了HALT模型,在外部测试队列中显示出比当前八个模型更好的判别性能(C指数,0.791)(C指数,0.529 - 0.627;均P<0.001)。如果病情最严重的患者(年龄>55岁,OFs≥3且乳酸≥2.5 mmol/L)接受高风险移植物(DCD且CIT>10小时),估计肝移植术后1年死亡率为85.6%。

解读

HALT模型显示出优于当前八个模型的预测能力,可能有助于肝移植候选者的选择和优化器官分配。尽管这些发现需要在前瞻性研究和不同患者群体中进行验证。

资助

本研究得到了中国国家自然科学基金、浙江省自然科学基金以及山东济南微生态生物医药实验室研究项目的资助。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eb9/12303012/7a7a99fb8f35/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eb9/12303012/b06f3c05507e/gr2.jpg
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New progress in HBV control and the cascade of health care for people living with HBV in China: evidence from the fourth national serological survey, 2020.中国乙肝控制新进展及乙肝感染者医疗保健级联服务:来自2020年第四次全国血清学调查的证据
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An integrated proteomics and metabolomics approach to assess graft quality and predict early allograft dysfunction after liver transplantation: a retrospective cohort study.
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