Establishment and evaluation of a novel and non-invasive diagnostic model on cirrhotic patients

Abstract

Objective To establish and evaluate a novel and non-invasive diagnostic model using routine laboratory serological indexes in cirrhotic patients. Methods A retrospective study was conducted on 1044 consecutive patients with hepatocellular carcinoma (HCC) treated by hepatectomy in the Affiliated Tumor Hospital of Guangxi Medical University from September 2013 to December 2016. These patients were divided into a training cohort (n=783) and a validation cohort (n=261) using the 3∶1 matching principle. Logistic regression analysis was used to identify independent risk factors related to occurrence of cirrhosis in the training cohort, and then a PPH score was established. The accuracy of the model in predicting cirrhosis in two groups was evaluated respectively by the area under the receiver operating characteristic curve (AUC) and goodness of fit, and compared with the following commonly used predictive systems: the model for end-stage liver disease (MELD) score, fibrosis index based on 4 factor score (FIB-4), Forns score and aspartate aminotransferase to platelet ratio index score (APRI). Results Univariate and multivariate Logistic regression analysis in the training cohort showed prothrombin time, platelet count and hepatitis B surface antigen positivity were closely related to occurrence of cirrhosis. The accuracy of the PPH score (AUC=0.705) in diagnosing cirrhosis in the training cohort was significantly better than the MELD score (AUC=0.557), APRI score (AUC=0.598), FIB-4 score (AUC=0.597) and Forns score (AUC=0.665). Similar results were obtained in the validation cohort (AUC: 0.702 vs 0.554 vs 0.624 vs 0.634 vs 0.580). The goodness of fit indicated that there was no significant difference between the actual and predicted values of cirrhosis in the two cohorts, and the model was in good agreement. Conclusions A novel and non-invasive model for the diagnosis of cirrhosis was successfully established. The accuracy of this model in diagnosing cirrhosis was better than the MELD, APRI, Fib-4 and Forns scores. This model has significance in guiding clinical treatment decision in HCC patients with cirrhosis. Key words: Carcinoma, hepatocellular; Liver cirrhosis; Biological markers; Non-invasive diagnosis model