Observational Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jul 28, 2025; 31(28): 108321
Published online Jul 28, 2025. doi: 10.3748/wjg.v31.i28.108321
Construction of a community-based primary screening and hospital-based confirmatory screening pathway in pediatric nonalcoholic fatty liver disease
Ming-Jie Yao, Yun-Fei Xing, Shu-Hong Liu, Ya-Fei Peng, Shu-Han Yang, Juan-Juan Chen, Jing-Min Zhao, Hui Wang
Ming-Jie Yao, Department of Anatomy and Embryology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
Yun-Fei Xing, Shu-Han Yang, Hui Wang, Department of Maternal and Child Health, School of Public Health, Peking University Health Science Center, Beijing 100191, China
Shu-Hong Liu, Department of Pathology and Hepatology, The Fifth Medical Center of PLA General Hospital, Beijing 100191, China
Ya-Fei Peng, Department of Nursing, Nursing School of Dalian Medical University, Dalian 116044, Liaoning Province, China
Juan-Juan Chen, Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450001, Henan Province, China
Jing-Min Zhao, Department of Pathology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing 100039, China
Co-first authors: Ming-Jie Yao and Yun-Fei Xing.
Co-corresponding authors: Jing-Min Zhao and Hui Wang.
Author contributions: Yao MJ, Wang H, and Zhao JM conceptualized and designed the research; Xing YF, Liu SH, Peng YF, Yang SH, and Chen JJ screened patients and acquired clinical data; Xing YF performed Data analysis; Liu SH, Peng YF, Chen JJ, and Yang SH, provided statistical guidance and material support; Xing YF and Yao MJ wrote the paper; Wang H and Zhao JM supervised the study; All authors critically revised the manuscript for important intellectual content. Yao MJ and Xing YF were both responsible for data collection and writing, and made critical and indispensable contributions to the completion of the project, so they are eligible to be co-first authors of the manuscript. Wang H and Zhao JM, as co-corresponding authors, played an essential and indispensable role in study design, data interpretation, and overall supervision. Both also provided funding support for the project.
Supported by National Natural Science Foundation of China, No. 82272433; Fujian Provincial Key Laboratory of Hepatic Drug Research, No. 2022-YF-0050; the Major Science and Technology Projects for Health of Zhejiang Province, No. WKJ-ZJ-2216; and the Cyrus Tang Foundation for Young Scholar, No. 2022 (2022-B126).
Institutional review board statement: This study was approved by the Institutional Review Board of Peking University, with approval No. IRB00001052-19081, dated 2020-09-24.
Informed consent statement: This was a retrospective study and the ethics committee agreed to exempt written informed consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Data sharing statement: Datasets related to the present study are available from the corresponding author upon reasonable request at huiwang@bjmu.edu.cn.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Hui Wang, PhD, Assistant Professor, Department of Maternal and Child Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, Beijing 100191, China. huiwang@bjmu.edu.cn
Received: April 18, 2025
Revised: May 12, 2025
Accepted: July 2, 2025
Published online: July 28, 2025
Processing time: 98 Days and 4.2 Hours
Abstract
BACKGROUND

Fibrosis is a critical event in the progression of pediatric nonalcoholic fatty liver disease (NAFLD).

AIM

To develop less invasive models based on machine learning (ML) to predict significant fibrosis in Chinese NAFLD children.

METHODS

In this cross-sectional study, 222 and 101 NAFLD children with available liver biopsy data were included in the development of screening models for tertiary hospitals and community health centers, respectively. Predictive factors were selected using least absolute shrinkage and selection operator regression and stepwise logistic regression analyses. Logistic regression (LR) and other ML models were applied to construct the prediction models.

RESULTS

Simplified indicators of the ATS and BIU indices were constructed for tertiary hospitals and community health centers, respectively. When models based on the ATS and BIU parameter combinations were constructed, the random forest (RF) model demonstrated higher screening accuracy compared to the LR model (0.80 and 0.79 for the RF model and 0.72 and 0.77 for the LR model, respectively). Using cutoff values of 90% for sensitivity and 90% for specificity, the RF models could effectively identify and exclude NAFLD children with significant fibrosis in the internal validation set (with positive predictive values and negative prediction values exceeding 0.80), which could prevent liver biopsy in 60% and 71.4% of NAFLD children, respectively.

CONCLUSION

This study developed new models for predicting significant fibrosis in NAFLD children in tertiary hospitals and community health centers, which can serve as preliminary screening tools to detect the risk population in a timely manner.

Keywords: Children; Nonalcoholic fatty liver disease; Significant fibrosis; Machine learning; Less invasive test

Core Tip: Fibrosis is a critical event in the progression of pediatric nonalcoholic fatty liver disease (NAFLD), and practical and efficient screening indices for early detection and referral in a large population are urgently needed. Different indices were generated for tertiary hospitals and community health centers based on the data of Chinese NAFLD children individually confirmed via liver biopsy. Serial tests were able to dramatically increase the positive predictive value. The sequential implementation of these less invasive screening predictors and referral systems could help physicians in accurately detecting the risk population accurately; however, broad age/ethnic range population validation is needed.