Accurate prediction of HCC risk after SVR in patients with hepatitis C cirrhosis based on longitudinal data.

ABSTRACT:

Background

Most existing predictive models of hepatocellular carcinoma (HCC) risk after sustained virologic response (SVR) are built on data collected at baseline and therefore have limited accuracy. The current study aimed to construct an accurate predictive model incorporating longitudinal data using a novel modeling strategy. The predictive performance of the longitudinal model was also compared with a baseline model.

Methods

A total of 400 patients with HCV-related cirrhosis who achieved SVR with direct-acting antivirals (DAA) were enrolled in the study. Patients were randomly divided into a training set (70%) and a validation set (30%). Informative features were extracted from the longitudinal variables and then put into the random survival forest (RSF) to develop the l

SUBMITTER: Zou Y 

PROVIDER: S-EPMC10676612 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature