Risk stratification of decompensated cirrhosis patients by Chronic Liver Failure Consortium scores: Classification and regression tree analysis

Yu Shi, Zheyue Shu, Wenjie Sun, Qiao Yang, Ye Yu, Gang Yang, Wei Wu, Si Chen, Wei Huang, Tingting Wang, Huadong Yan
Hepatology Research: the Official Journal of the Japan Society of Hepatology 2017, 47 (4): 328-337

AIM: Decompensated cirrhosis patients have greatly variable prognosis. The aim of the study was to carry out a risk stratification for those patients by Chronic Liver Failure (CLIF) Consortium scores.

METHODS: The performance of CLIF Consortium acute-on-chronic liver failure scores (CLIF-C ACLFs) and CLIF Consortium Acute Decompensation scores (CLIF-C ADs) were validated in 209 patients with ACLF and 1245 patients without ACLF at admission from the Ningbo Cohort. A classification and regression tree (CRT) analysis by CLIF-C ACLFs/CLIF-C ADs was carried out to stratify death risk among patients.

RESULTS: The CLIF-C ACLFs and CLIF-C ADs showed higher predictive accuracy than Model for End-stage Liver Disease (MELD) scores, MELD plus serum sodium (MELD-Na) scores, and Child-Turcotte-Pugh classification (CP) at main time points (28, 90, 180, and 365 days), determined by area under the receiver-operating characteristic curve and concordance index in ACLF and no-ACLF patients at admission. The CRT analysis categorized ACLF patients into two groups (advanced and early ACLF), and no-ACLF patients into three groups (high-, medium-, and low-risk AD) according to risk of death. However, early ACLF and high-risk AD patients had comparable mortality at the main time points. The CRT model had a higher area under the receiver-operating characteristic curve than MELDs, MELD-Nas, and CPs in predicting prognosis in all patients.

CONCLUSIONS: The CLIF-C ACLF and CLIF-C AD are better prognostic scores than MELD, MELD-Na, and CP in predicting mortality of ACLF and no-ACLF patients. A combined use of CLIF- Sequential Organ Failure Assessment, CLIF-C ACLFs, and CLIF-C ADs could identify cirrhosis patients at high death risk and assist clinical decisions for management.

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