A decision tree model to predict liver cirrhosis in hepatocellular carcinoma patients: a retrospective study.

ABSTRACT:

Background

The severity of liver cirrhosis in hepatocellular carcinoma (HCC) patients is essential for determining the scope of surgical resection. It also affects the long-term efficacy of systemic anti-tumor therapy and transcatheter arterial chemoembolization (TACE). Non-invasive tools, including aspartate aminotransferase to platelet ratio index (APRI), fibrosis-4 (FIB-4), and γ-glutamyl transferase to platelet ratio (GPR), are less accurate in predicting cirrhosis in HCC patients. We aimed to build a novel decision tree model to improve diagnostic accuracy of liver cirrhosis.

Patients and methods

The Mann-Whitney U test, χ² test, and multivariate logistic regression analysis were used to identify independent cirrhosis predictors. A decision tree model was dev

SUBMITTER: Zhou Z 

PROVIDER: S-EPMC10460570 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature