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.

IF 10 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL
EClinicalMedicine Pub Date : 2025-07-17 eCollection Date: 2025-08-01 DOI:10.1016/j.eclinm.2025.103365
Li Zhuang, Yimou Lin, Yu Jia, Jun Fang, Yujian Zheng, Taishi Fang, Meiching Ong, Aibo Mu, Jiaxing Zhu, Mengchao Wang, Dong Zhao, Feiwen Deng, Qiucheng Lei, Leibo Xu, Zuozhong Yang, Qiang Sun, Wei Qu, Chenwei Xu, Zhijun Zhu, Chuanjiang Li, Hanyu Jiang, Jimin Liu, Xiaoshun He, Shusen Zheng, Zhiyong Guo, Qi Ling
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引用次数: 0

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 p < 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 p < 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 p < 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.

一种预测急性慢性乙型肝炎肝衰竭移植后1年死亡率的新型预后模型的开发和验证:一项全国性、多中心、队列研究
背景:肝移植(LT)为乙型肝炎病毒相关的急性-慢性肝衰竭(HBV-ACLF)提供了一种潜在的治疗方法。我们旨在开发并外部验证一个预测HBV-ACLF患者lt后1年死亡率的预后模型。方法:这项回顾性的、全国性的、观察性队列研究在中国10个大容量肝移植中心进行,筛选了2015年1月至2021年12月期间接受原发性肝移植的4378名成年患者,根据COSSH-ACLF标准(根据器官衰竭的数量分为三个ACLF等级)纳入了HBV-ACLF患者。HBV-ACLF LT (HALT)模型是在衍生队列中建立的,并在外部测试队列中得到验证。衍生队列来自一个省(浙江)的两个LT中心。外部检测队列来自两个省的八个LT中心。为了建立模型,采用单变量Cox回归分析来确定与肝移植后1年死亡率相关的危险因素。输入单变量p < 0.05的变量进行最小绝对收缩和选择算子(Lasso)分析,进一步进行特征选择。使用10倍交叉验证选择Lasso模型的最优lambda(特征数惩罚)。基于Lasso分析选择的危险因素,采用多变量Cox回归构建HALT模型。主要结局是术后1年生存率。次要结局是术后短期(28天和90天)和长期生存(3年和5年)。采用受试者工作特征曲线和c指标值与其他8个模型(COSSH-ACLF II、COSSH-ACLF、cliff - c ACLF、AARC、MELD、MELD- na、SALT-M和TAM评分)进行比较。基于受体因素(年龄、器官衰竭次数[of]、乳酸)和移植物因素(循环死亡后捐献[DCD]和冷缺血时间[CIT]),我们开发了一个nomogram来分析不同移植物-受体组合的主要结局的概率。研究结果:2015年1月1日至2021年12月1日,纳入668例患者(衍生队列,n = 418;外部检测队列,n = 250),术后28天、90天、1年、3年和5年生存率分别为88.0%、81.1%、77.5%、75.6%和72.1%。在衍生队列中,三个受体因素(年龄、of数目和动脉乳酸浓度)以及两个移植物参数(DCD和CIT)与肝移植后1年死亡率独立相关(均p < 0.05)。据此建立HALT模型,其判别性能(C-index, 0.791)优于外部测试队列中现有的8个模型(C-index, 0.529-0.627;均p < 0.001)。如果病情最严重的患者(年龄0 ~ 55岁,OFs≥3,乳酸≥2.5 mmol/L)接受高危移植物(DCD和CIT >10 h),估计lt后1年死亡率为85.6%。结论:HALT模型比目前的8个模型显示出更好的预测能力,可能有助于LT候选人的选择和最佳器官分配。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。基金资助:国家自然科学基金、浙江省自然科学基金、济南微生态生物医学山东省实验室研究项目资助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
EClinicalMedicine
EClinicalMedicine Medicine-Medicine (all)
CiteScore
18.90
自引率
1.30%
发文量
506
审稿时长
22 days
期刊介绍: eClinicalMedicine is a gold open-access clinical journal designed to support frontline health professionals in addressing the complex and rapid health transitions affecting societies globally. The journal aims to assist practitioners in overcoming healthcare challenges across diverse communities, spanning diagnosis, treatment, prevention, and health promotion. Integrating disciplines from various specialties and life stages, it seeks to enhance health systems as fundamental institutions within societies. With a forward-thinking approach, eClinicalMedicine aims to redefine the future of healthcare.
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