Development and validation of a clinical data-based diagnostic model for neonatal intrahepatic cholestasis caused by citrin deficiency

doi:10.3748/wjg.121360

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 32, Issue 46

This Article

(4)

(5)

(0)

(52)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Gastroenterology

ISSN

1007-9327

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastroenterol. Dec 14, 2026; 32(46): 121360
Published online Dec 14, 2026. doi: 10.3748/wjg.121360

Development and validation of a clinical data-based diagnostic model for neonatal intrahepatic cholestasis caused by citrin deficiency

Tao Jiang, Xiao-Mei Qin, Yuan-Wei Liu, Shuang-Jie Li, Na Liu, Wen-Xian Ouyang, Song-Xu Peng

Tao Jiang, Xiao-Mei Qin, Shuang-Jie Li, Na Liu, Wen-Xian Ouyang, Department of Hepatopathy Center, The Affiliated Children’s Hospital of Xiangya School of Medicine, Central South University (Hunan Children’s Hospital), Changsha 410007, Hunan Province, China

Yuan-Wei Liu, Department of Pediatric Medicine, The First People’s Hospital of Chenzhou, Chenzhou 423000, Hunan Province, China

Song-Xu Peng, Department of Maternal and Child Health, Xiangya School of Public Health, Central South University, Changsha 410078, Hunan Province, China

Co-first authors: Tao Jiang and Xiao-Mei Qin.

Co-corresponding authors: Wen-Xian Ouyang and Song-Xu Peng.

Author contributions: Jiang T and Qin XM participated in the conception and design of the study and were involved in the acquisition, analysis, or interpretation of data; Jiang T wrote the manuscript; Li SJ, Liu YW and Liu N designed the research study and performed the research; Ouyang WX and Peng SX accessed and verified the study data. All authors critically reviewed and provided final approval of the manuscript. All authors were responsible for the decision to submit the manuscript for publication. The collaboration and sharing of tasks crucial to the conduction and completion of the study by Jiang T and Qin XM underlie their designation as co-first authors. The equal contributions of Ouyang WX and Peng SX formed the logistical core of the study and were critical for its ultimate publication, underlying their merit as co-corresponding authors.

AI contribution statement: I assume full responsibility and accountability for the integrity, accuracy, originality, and scientific validity of the manuscript and all submitted materials. And I do not use artificial intelligence tools in the preparation of the manuscript and answering the reviewers.

Supported by Hunan Provincial Clinical Research Center for Pediatric Liver Diseases, Technology Department of Hunan Province, No. 2020SK4002; and Clinical Research (Translation) Center of Hunan Children’s Hospital.

Institutional review board statement: The study was approved by the Ethics Committee of Hunan Children’s Hospital (No. KS2026-173).

Informed consent statement: The requirement for informed consent was waived due to the retrospective nature of the study.

Conflict-of-interest statement: The authors have no conflicts of interest to declare.

Data sharing statement: The dataset generated and analyzed during the current study is available from the corresponding author on reasonable request.

Corresponding author: Wen-Xian Ouyang, MD, Department of Hepatopathy Center, The Affiliated Children’s Hospital of Xiangya School of Medicine, Central South University (Hunan Children’s Hospital), No. 86 of Ziyuan Road, Changsha 410007, Hunan Province, China. 3441325922@qq.com

Received: March 24, 2026
Revised: May 22, 2026
Accepted: August 20, 2026
Published online: December 14, 2026
Processing time: 210 Days and 23.6 Hours

Abstract

BACKGROUND

Neonatal intrahepatic cholestasis caused by citrin deficiency (NICCD) is a leading cause of infantile chronic liver disease, with the potential to progress to severe complications such as cirrhosis or liver failure. Therefore, early diagnosis and timely intervention are critical. Due to the limitations of newborn screening and genetic testing, novel diagnostic models are needed to improve the early diagnosis of NICCD.

AIM

To develop and validate a diagnostic model using clinical data to facilitate the early diagnosis of NICCD.

METHODS

This retrospective study developed and validated an early diagnostic model for NICCD using data from Hunan Children’s Hospital (2014-2025), including 170 patients with NICCD (NICCD group) and 196 patients with cholestatic hepatitis attributed to other etiologies (control group). Binary logistic regression was employed to construct the combined model. Model performance was evaluated using receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow test, with internal validation performed via bootstrapping. The optimal threshold was established using Youden’s index, with external validation conducted on 39 NICCD cases and 59 controls from First People’s Hospital of Chenzhou.

RESULTS

This study identified 22 differential indicators, with age, albumin (ALB), lactate, and international normalized ratio (INR) selected via univariate and multivariate logistic regression. A joint binary logistic model was developed: Logit (p) = 1.518 + 1.427 × age - 0.423 × ALB + 0.596 × lactate + 6.639 × INR. A cutoff of 0.51 yielded 0.95 sensitivity and 0.97 specificity for NICCD diagnosis. The model achieved an area under the ROC (AUROC) of 0.99 [95% confidence interval (CI): 0.99-1.00], with a Hosmer-Lemeshow goodness-of-fit χ² value of 1.834 (P = 0.986), indicating good discrimination and calibration. Bootstrap internal validation yielded an AUROC of 0.966 (95%CI: 0.948-0.982). The model achieved an AUROC of 0.90 (95%CI: 0.82-0.98) in the validation set.

CONCLUSION

This study developed and validated a high-performing diagnostic model for NICCD using readily available clinical data.

Keywords: Clinical data; Diagnostic model; Neonatal intrahepatic cholestasis caused by citrin deficiency; Binary logistic regression; Early diagnosis

Core Tip: This study developed a novel diagnostic model for citrin deficiency-induced neonatal intrahepatic cholestasis based on clinical variables, representing a new approach in the literature. The model’s excellent diagnostic performance suggests that it could significantly assist in clinical decision-making.