An MLP Classifier for Prediction of HBV-Induced Liver Cirrhosis Using Routinely Available Clinical Parameters

作者：Cao, Yuan; Hu, Zhi-De; Liu, Xiao-Fei; Deng, An-Mei^*; Hu, Cheng-Jin

来源：Disease Markers, 2013, 2013(6): 653-660.

DOI：10.1155/2013/127962

• PLATELET RATIO INDEX
• CELL DISTRIBUTION WIDTH
• CHRONIC HEPATITIS-B
• SIMPLE NONINVASIVE INDEX
• SIGNIFICANT FIBROSIS
• C PATIENTS
• ASPARTATE-AMINOTRANSFERASE
• TRANSIENT ELASTOGRAPHY
• LARGE COHORT
• APRI

Background. Liver cirrhosis (LC) is the final stage of most of chronic liver diseases and is almost caused by chronic hepatitis B (CHB) in China. Liver biopsy is the reference method for the evaluation of liver cirrhosis. However, it is an invasive procedure with inherent risk. The aim of this study was to construct a new classifier based on the routine clinical markers for the prediction of HBV-induced LC. Subjects and Methods. We collected routine clinical parameters from 124 LC patients with CHB and 115 with CHB. Training set (n = 120) and test set (n = 119) were built for model construction and evaluation, respectively. Results. We describe a new classifier, MLP, for prediction of LC with CHB. MLP was built with seven routinely available clinical parameters, including age, ALT, AST, PT, PLT, HGB, and RDW. With optimal cutoff, we obtained a sensitivity of 95.2%, a specificity of 84.2%, and an overall accuracy of 89.9% on an independent test set, which were superior to those of FIB-4 and APRI. Conclusions. Our study suggests that the MLP classifier can be implemented for discriminating LC and non-LC cohorts by using machine learning method based on the routine available clinical parameters. It could be used for clinical practice in HBV-induced LC assessment.

• 出版日期2013
• 单位中国人民解放军第二军医大学; 中国人民解放军济南军区总医院