A novel dynamic model for predicting outcome in patients with hepatitis B virus related acute-on-chronic liver failure

Ran Xue, Zhonghui Duan, Haixia Liu, Li Chen, Hongwei Yu, Meixin Ren, Yueke Zhu, Chenggang Jin, Tao Han, Zhiliang Gao, Qinghua Meng

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Aim: It is challenging to predict the outcome of patients with hepatitis B virus related acute-on-chronic liver failure (HBV-ACLF) through existing prognostic models. Our aim was to establish a novel dynamic model to improve the predictive efficiency of 30-day mortality in HBV-ACLF patients.

Methods: 305 patients who were diagnosed as HBV-ACLF (derivation cohort, n=211; validation cohort, n=94) were included in this study. The HBV-ACLF dynamic (HBV-ACLFD) model was constructed based on the daily levels of predictive variables in 7 days after diagnosis combined with baseline risk factors by multivariate logistic regression analysis. The HBV-ACLFD model was compared with the Child-Turcotte-Pugh (CTP) score, end-stage liver disease (MELD) score, and MELD within corporation of serum sodium (MELD-Na) score by the area under the receiver-operating characteristic curves (AUROC).

Results: The HBV-ACLFD model demonstrated excellent discrimination with AUROC of 0.848 in the derivation cohort and of 0.813 in the validation cohort (p=0.620). The performance of the HBV-ACLFD model appeared to be superior to MELD score, MELD-Na score and CTP score (P<0.0001).

Conclusion: The HBV-ACLFD model can accurately predict 30-day mortality in patients with HBV-ACLF, which is helpful to select appropriate clinical procedures, so as to relieve the social and economic burden.

Original languageEnglish (US)
Pages (from-to)108970-108980
Number of pages11
JournalOncotarget
Volume8
Issue number65
DOIs
StatePublished - Dec 12 2017

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