Machine learning predicts post-transplant muscle loss in hepatocellular carcinoma patients without sarcopenia.

ABSTRACT:

Objective

Developing a machine learning model to predict post-transplant muscle loss in hepatocellular carcinoma patients.

Background

Liver transplantation is an effective treatment for selected HCC patients. However, severe muscle loss after liver transplantation is significantly associated with increased risk of mortality and recurrence. However, effective predictive methods remain inadequate.

Methods

This study collected data from hepatocellular carcinoma patients who underwent liver transplantation over the past 2015 to 2020 at two hospitals. Propensity score matching and Cox regression analysis were conducted to establish muscle loss as an independent risk factor for recurrence. To construct the optimal predictive model for post-transplant muscle loss, we compare

SUBMITTER: Chen J 

PROVIDER: S-EPMC12522249 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature