Gao Fangyuan, Sun Le, Ye Xieqiong, Liu Yao, Liu Huimin, Geng Mingfan, Li Xiaoshu, Yang Xue, Li Yuxin, Wang Rui, Chen Jialiang, Wan Gang, Jiang Yuyong, Wang Xianbo
aCenter of Integrative Medicine bStatistics Room, Beijing Ditan Hospital, Capital Medical University cDepartment of Gastroenterology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Eur J Gastroenterol Hepatol. 2017 Jun;29(6):669-678. doi: 10.1097/MEG.0000000000000854.
The CANONIC study proposed the Chronic Liver Failure Consortium acute-on-chronic liver failure (CLIF-C ACLF) prognostic model at the European Association for the Study of the Liver-CLIF diagnosis. This study aimed to develop and validate a prognostic model for predicting the short-term mortality of hepatitis B virus (HBV) ACLF as defined by the Asia-Pacific Association for the Study of the Liver.
A retrospective cohort of 381 HBV ACLF patients and a prospective cohort of 192 patients were included in this study. Independent predictors of disease progression were determined using univariate and multivariate Cox proportional hazard regression analysis, and a regression model for predicting prognosis was established. Patient survival was estimated by Kaplan-Meier analysis and subsequently compared by log-rank tests. The area under the receiver operating characteristic curve was used to compare the performance of various current prognostic models.
Our model was constructed with five independent risk factors: hepatic encephalopathy, international normalized ratio, neutrophil-lymphocyte ratio, age, and total bilirubin, termed as the HINAT ACLF model, which showed the strongest predictive values compared with CLIF-C ACLF, CLIF-C Organ Failure, Sequential Organ Failure Assessment, CLIF-Sequential Organ Failure Assessment, Model for End-stage Liver Disease, Model for End-stage Liver Disease-sodium, and Child-Turcotte-Pugh scores; this model reduced the corresponding prediction error rates at 28 and 90 days by 16.4-54.5% after ACLF diagnosis in both the derivation cohort and the validation cohorts.
The HINAT ACLF model can accurately predict the short-term mortality of patients with HBV ACLF as defined by Asia-Pacific Association for the Study of the Liver.
CANONIC研究在欧洲肝脏研究协会-慢性肝衰竭联盟（CLIF-C）对急性慢性肝衰竭（CLIF-C ACLF）的诊断基础上提出了该预后模型。本研究旨在开发并验证一种用于预测亚太肝脏研究协会所定义的乙型肝炎病毒（HBV）相关慢加急性肝衰竭短期死亡率的预后模型。
本研究纳入了381例HBV相关慢加急性肝衰竭患者的回顾性队列以及192例患者的前瞻性队列。使用单因素和多因素Cox比例风险回归分析确定疾病进展的独立预测因素，并建立预测预后的回归模型。通过Kaplan-Meier分析估计患者生存率，随后通过对数秩检验进行比较。采用受试者工作特征曲线下面积比较各种现有预后模型的性能。
我们的模型由五个独立风险因素构建而成：肝性脑病、国际标准化比值、中性粒细胞与淋巴细胞比值、年龄和总胆红素，称为HINAT ACLF模型，与CLIF-C ACLF、CLIF-C器官衰竭、序贯器官衰竭评估、CLIF-序贯器官衰竭评估、终末期肝病模型、终末期肝病-钠模型以及Child-Turcotte-Pugh评分相比，该模型显示出最强的预测价值；在推导队列和验证队列中，该模型在慢加急性肝衰竭诊断后28天和90天降低了相应的预测错误率，降低幅度为16.4%-54.5%。
HINAT ACLF模型能够准确预测亚太肝脏研究协会所定义的HBV相关慢加急性肝衰竭患者的短期死亡率。
