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Nomogram to Predict the Survival of Chinese Patients with Alcohol-Related Liver Disease
Author(s) -
Fangfang Duan,
Chen Liu,
Yuwei Liu,
Chunyan Chang,
Hang Zhai,
Huichun Xing,
Jun Cheng,
Song Yang
Publication year - 2021
Publication title -
canadian journal of gastroenterology and hepatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.921
H-Index - 65
eISSN - 2291-2797
pISSN - 2291-2789
DOI - 10.1155/2021/4073503
Subject(s) - nomogram , medicine , proportional hazards model , cohort , liver disease , liver cancer , cirrhosis , concordance , hazard ratio , survival analysis , oncology , surgery , cancer , confidence interval
Objectives Alcohol-related liver disease is an increasing public health burden in China, but there is a lack of models to predict its prognosis. This study established a nomogram for predicting the survival of Chinese patients with alcohol-related liver disease (ALD).Methods Hospitalized alcohol-related liver disease patients were retrospectively enrolled from 2015 to 2018 and followed up for 24 months to evaluate survival profiles. A total of 379 patients were divided into a training cohort ( n  = 265) and validation cohort ( n  = 114). Cox proportional hazard survival analysis identified survival factors of the patients in the training cohort. A nomogram was built and internally validated.Results The 3-month, 6-month, 12-month, and 24-month survival rates for the training cohort were 82.6%, 81.1%, 74.3%, and 64.5%, respectively. The Cox analysis showed relapse ( P =0.001), cirrhosis ( P =0.044), liver cancer ( P < 0.001), and a model for end-stage liver diseases score of ≥21 ( P =0.041) as independent prognostic factors. A nomogram was built, which predicted the survival of patients in the training cohort with a concordance index of 0.749 and in the internal validation cohort with a concordance index of 0.756.Conclusion The long-term survival of Chinese alcohol-related liver disease patients was poor with a 24-month survival rate of 64.5%. Relapse, cirrhosis, liver cancer, and a model for end-stage liver disease score of ≥21 were independent risk factors for those patients. A nomogram was developed and internally validated for predicting the probability of their survival at different time points.

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