Machine learning model for predicting hepatitis C seroconversion in methadone maintenance patients in China.

ABSTRACT:

Introduction

Hepatitis C virus (HCV) infection is a substantial public health concern, particularly among individuals with opioid addiction. The methadone maintenance treatment (MMT) programmes serve as a harm reduction strategy to mitigate HIV disease spread, yet the risk of HCV infection remains high within these settings. Accurate risk prediction for HCV seroconversion is therefore crucial for improving patient outcomes.

Methods

We collected data from 1547 individuals with opioid use disorder who entered the MMT programme from May 2005 to October 2023 in Shanghai, China, and 283 individuals from July 2006 to October 2023 in Mianyang, China, whose HCV infection status was monitored. Shanghai data were divided into training and validation sets in a 7:3 ratio, with 70% of th

SUBMITTER: Lu X 

PROVIDER: S-EPMC12410665 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature