Development and validation of a prognostic model for acute-on-chronic hepatitis B liver failure

AIMThe 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...

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Veröffentlicht in:European journal of gastroenterology & hepatology 2017-06, Vol.29 (6), p.669-678
Hauptverfasser: 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
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container_end_page 678
container_issue 6
container_start_page 669
container_title European journal of gastroenterology & hepatology
container_volume 29
creator 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
description AIMThe 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. PATIENTS AND METHODSA 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. RESULTSOur model was constructed with five independent risk factorshepatic 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. CONCLUSIONThe 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.
doi_str_mv 10.1097/MEG.0000000000000854
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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. PATIENTS AND METHODSA 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. RESULTSOur model was constructed with five independent risk factorshepatic 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. CONCLUSIONThe 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.</description><identifier>ISSN: 0954-691X</identifier><identifier>EISSN: 1473-5687</identifier><identifier>DOI: 10.1097/MEG.0000000000000854</identifier><identifier>PMID: 28195876</identifier><language>eng</language><publisher>England: Copyright Wolters Kluwer Health, Inc. All rights reserved</publisher><subject>Acute-On-Chronic Liver Failure - diagnosis ; Acute-On-Chronic Liver Failure - mortality ; Acute-On-Chronic Liver Failure - virology ; Adult ; Area Under Curve ; Chi-Square Distribution ; Decision Support Techniques ; Female ; Hepatitis B, Chronic - diagnosis ; Hepatitis B, Chronic - mortality ; Hepatitis B, Chronic - virology ; Humans ; Kaplan-Meier Estimate ; Male ; Middle Aged ; Multivariate Analysis ; Organ Dysfunction Scores ; Predictive Value of Tests ; Prognosis ; Proportional Hazards Models ; Reproducibility of Results ; Retrospective Studies ; Risk Assessment ; Risk Factors ; ROC Curve ; Time Factors</subject><ispartof>European journal of gastroenterology &amp; hepatology, 2017-06, Vol.29 (6), p.669-678</ispartof><rights>Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3564-5a68bcff12086bd05eadb113e2386790e010788b35dd7dc81cafa1329fa7203c3</citedby><cites>FETCH-LOGICAL-c3564-5a68bcff12086bd05eadb113e2386790e010788b35dd7dc81cafa1329fa7203c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28195876$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gao, Fangyuan</creatorcontrib><creatorcontrib>Sun, Le</creatorcontrib><creatorcontrib>Ye, Xieqiong</creatorcontrib><creatorcontrib>Liu, Yao</creatorcontrib><creatorcontrib>Liu, Huimin</creatorcontrib><creatorcontrib>Geng, Mingfan</creatorcontrib><creatorcontrib>Li, Xiaoshu</creatorcontrib><creatorcontrib>Yang, Xue</creatorcontrib><creatorcontrib>Li, Yuxin</creatorcontrib><creatorcontrib>Wang, Rui</creatorcontrib><creatorcontrib>Chen, Jialiang</creatorcontrib><creatorcontrib>Wan, Gang</creatorcontrib><creatorcontrib>Jiang, Yuyong</creatorcontrib><creatorcontrib>Wang, Xianbo</creatorcontrib><title>Development and validation of a prognostic model for acute-on-chronic hepatitis B liver failure</title><title>European journal of gastroenterology &amp; hepatology</title><addtitle>Eur J Gastroenterol Hepatol</addtitle><description>AIMThe 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. PATIENTS AND METHODSA 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. RESULTSOur model was constructed with five independent risk factorshepatic 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. CONCLUSIONThe 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.</description><subject>Acute-On-Chronic Liver Failure - diagnosis</subject><subject>Acute-On-Chronic Liver Failure - mortality</subject><subject>Acute-On-Chronic Liver Failure - virology</subject><subject>Adult</subject><subject>Area Under Curve</subject><subject>Chi-Square Distribution</subject><subject>Decision Support Techniques</subject><subject>Female</subject><subject>Hepatitis B, Chronic - diagnosis</subject><subject>Hepatitis B, Chronic - mortality</subject><subject>Hepatitis B, Chronic - virology</subject><subject>Humans</subject><subject>Kaplan-Meier Estimate</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>Organ Dysfunction Scores</subject><subject>Predictive Value of Tests</subject><subject>Prognosis</subject><subject>Proportional Hazards Models</subject><subject>Reproducibility of Results</subject><subject>Retrospective Studies</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>ROC Curve</subject><subject>Time Factors</subject><issn>0954-691X</issn><issn>1473-5687</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1PxCAQhonR6PrxD4zh6KUKpQV69GNdTTReNPFGKAxulZYV2t34761ZNcaDM4c5zPu-M3kQOqTkhJJKnN5NZyfkd8my2EATWgiWlVyKTTQhVVlkvKJPO2g3pRdCqGBUbKOdXNKqlIJPkLqEJfiwaKHrse4sXmrfWN03ocPBYY0XMTx3IfWNwW2w4LELEWsz9JCFLjPzGLpxNYfF6OmbhM-xb5YQsdONHyLsoy2nfYKDr7mHHq-mDxfX2e397Obi7DYzrORFVmoua-MczYnktSUlaFtTyiBnkouKAKFESFmz0lphjaRGO01ZXjktcsIM20PH69zx37cBUq_aJhnwXncQhqSo5GNTxvgoLdZSE0NKEZxaxKbV8V1Roj7RqhGt-ot2tB19XRjqFuyP6ZvlKJBrwSr4HmJ69cMKopqD9v38_-wPe-KF0A</recordid><startdate>20170601</startdate><enddate>20170601</enddate><creator>Gao, Fangyuan</creator><creator>Sun, Le</creator><creator>Ye, Xieqiong</creator><creator>Liu, Yao</creator><creator>Liu, Huimin</creator><creator>Geng, Mingfan</creator><creator>Li, Xiaoshu</creator><creator>Yang, Xue</creator><creator>Li, Yuxin</creator><creator>Wang, Rui</creator><creator>Chen, Jialiang</creator><creator>Wan, Gang</creator><creator>Jiang, Yuyong</creator><creator>Wang, Xianbo</creator><general>Copyright Wolters Kluwer Health, Inc. All rights reserved</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20170601</creationdate><title>Development and validation of a prognostic model for acute-on-chronic hepatitis B liver failure</title><author>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</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3564-5a68bcff12086bd05eadb113e2386790e010788b35dd7dc81cafa1329fa7203c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Acute-On-Chronic Liver Failure - diagnosis</topic><topic>Acute-On-Chronic Liver Failure - mortality</topic><topic>Acute-On-Chronic Liver Failure - virology</topic><topic>Adult</topic><topic>Area Under Curve</topic><topic>Chi-Square Distribution</topic><topic>Decision Support Techniques</topic><topic>Female</topic><topic>Hepatitis B, Chronic - diagnosis</topic><topic>Hepatitis B, Chronic - mortality</topic><topic>Hepatitis B, Chronic - virology</topic><topic>Humans</topic><topic>Kaplan-Meier Estimate</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Multivariate Analysis</topic><topic>Organ Dysfunction Scores</topic><topic>Predictive Value of Tests</topic><topic>Prognosis</topic><topic>Proportional Hazards Models</topic><topic>Reproducibility of Results</topic><topic>Retrospective Studies</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>ROC Curve</topic><topic>Time Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gao, Fangyuan</creatorcontrib><creatorcontrib>Sun, Le</creatorcontrib><creatorcontrib>Ye, Xieqiong</creatorcontrib><creatorcontrib>Liu, Yao</creatorcontrib><creatorcontrib>Liu, Huimin</creatorcontrib><creatorcontrib>Geng, Mingfan</creatorcontrib><creatorcontrib>Li, Xiaoshu</creatorcontrib><creatorcontrib>Yang, Xue</creatorcontrib><creatorcontrib>Li, Yuxin</creatorcontrib><creatorcontrib>Wang, Rui</creatorcontrib><creatorcontrib>Chen, Jialiang</creatorcontrib><creatorcontrib>Wan, Gang</creatorcontrib><creatorcontrib>Jiang, Yuyong</creatorcontrib><creatorcontrib>Wang, Xianbo</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of gastroenterology &amp; hepatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gao, Fangyuan</au><au>Sun, Le</au><au>Ye, Xieqiong</au><au>Liu, Yao</au><au>Liu, Huimin</au><au>Geng, Mingfan</au><au>Li, Xiaoshu</au><au>Yang, Xue</au><au>Li, Yuxin</au><au>Wang, Rui</au><au>Chen, Jialiang</au><au>Wan, Gang</au><au>Jiang, Yuyong</au><au>Wang, Xianbo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development and validation of a prognostic model for acute-on-chronic hepatitis B liver failure</atitle><jtitle>European journal of gastroenterology &amp; hepatology</jtitle><addtitle>Eur J Gastroenterol Hepatol</addtitle><date>2017-06-01</date><risdate>2017</risdate><volume>29</volume><issue>6</issue><spage>669</spage><epage>678</epage><pages>669-678</pages><issn>0954-691X</issn><eissn>1473-5687</eissn><abstract>AIMThe 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. PATIENTS AND METHODSA 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. RESULTSOur model was constructed with five independent risk factorshepatic 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. CONCLUSIONThe 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.</abstract><cop>England</cop><pub>Copyright Wolters Kluwer Health, Inc. All rights reserved</pub><pmid>28195876</pmid><doi>10.1097/MEG.0000000000000854</doi><tpages>10</tpages></addata></record>
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subjects Acute-On-Chronic Liver Failure - diagnosis
Acute-On-Chronic Liver Failure - mortality
Acute-On-Chronic Liver Failure - virology
Adult
Area Under Curve
Chi-Square Distribution
Decision Support Techniques
Female
Hepatitis B, Chronic - diagnosis
Hepatitis B, Chronic - mortality
Hepatitis B, Chronic - virology
Humans
Kaplan-Meier Estimate
Male
Middle Aged
Multivariate Analysis
Organ Dysfunction Scores
Predictive Value of Tests
Prognosis
Proportional Hazards Models
Reproducibility of Results
Retrospective Studies
Risk Assessment
Risk Factors
ROC Curve
Time Factors
title Development and validation of a prognostic model for acute-on-chronic hepatitis B liver failure
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