Next Article in Journal
Flow-Controlled Ventilation as a Rescue Strategy in Advanced COVID-19 ARDS: A Retrospective Observational Study
Previous Article in Journal
Clinical and Perioperative Determinants of Postoperative Pneumonia After Craniotomy for Tumor Resection
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCM
Volume 15
Issue 12
10.3390/jcm15124438
jcm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Systematic Review

Prediction Models and Risk Factors for Steroid Resistance in Children with Nephrotic Syndrome: A Systematic Review and Meta-Analysis

by
Yuanhui Hu
1,2,3,4,5,
Zehui Zhang
5,
Sha Diao
1,2,3,4,
Yannan Guo
4,6,
Yangtingting Gao
5,
Zheng Xu
5,
Qilin Peng
7,
Yao Xu
5,
Zhenyan Bo
1,2,3,4,
Linan Zeng
1,2,3,4,8,
Liang Huang
1,2,3,4,
Jingjing Chen
1,2,3,4,
Yizhun Zhu
9,
Hailong Li
1,2,3,4,* and
Lingli Zhang
1,2,3,4,8,10,*
1
Department of Pharmacy/Evidence-Based Pharmacy Center, West China Second University Hospital, Sichuan University, No.20, Section 3, Renmin South Road, Wuhou District, Chengdu 610041, China
2
Children’s Medicine Key Laboratory of Sichuan Province, No.20, Section 3, Renmin South Road, Wuhou District, Chengdu 610041, China
3
NMPA Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, No.20, Section 3, Renmin South Road, Wuhou District, Chengdu 610041, China
4
Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, No.20, Section 3, Renmin South Road, Wuhou District, Chengdu 610041, China
5
West China School of Pharmacy, Sichuan University, No.17, Section 3, Renmin South Road, Wuhou District, Chengdu 610041, China
6
Department of Pediatrics, West China Second University Hospital, Sichuan University, No.20, Section 3, Renmin South Road, Wuhou District, Chengdu 610041, China
7
West China School of Medicine, Sichuan University, No.17, Section 3, Renmin South Road, Wuhou District, Chengdu 610041, China
8
West China Biomedical Big Data Center, West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu 610041, China
9
School of Pharmacy, Macau University of Science and Technology, No.100-460, Avenida Wai Long, Taipa, Macao 999078, China
10
Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu 610041, China
*
Authors to whom correspondence should be addressed.
J. Clin. Med. 2026, 15(12), 4438; https://doi.org/10.3390/jcm15124438 (registering DOI)
Submission received: 14 April 2026 / Revised: 28 May 2026 / Accepted: 3 June 2026 / Published: 8 June 2026
(This article belongs to the Section Clinical Pediatrics)
Browse Figure
Versions Notes

Abstract

Background: Steroid resistance indicates poor prognosis in pediatric nephrotic syndrome, but predictive models and risk factors for steroid-resistant nephrotic syndrome (SRNS) remain poorly understood. Methods: We searched PubMed, Embase, Scopus, CNKI, SinoMed, Wanfang, and VIP (inception to 1 March 2025) for studies developing SRNS prediction models or identifying risk factors. Odds ratios and AUC were pooled using random-effects meta-analysis. Risk of bias was assessed with PROBAST and Newcastle-Ottawa Scale. Results: Out of 2264 studies, 23 were included. Prediction models were mainly developed using logistic regression (16/17, 94.1%). The most frequently reported predictors included erythrocyte sedimentation rate and vitamin D binding protein. The reported AUC ranged from 0.75 to 0.88. Only one model had undergone external validation with an accuracy of 0.94. A total of 22 independent risk factors were identified, five of which—low birth weight, decreased urine output, hypertension, serum albumin, and serum IgM—were not in existing models. In total, 76% of model studies and 26% of risk factor analyses were at high or moderate risk of bias. Conclusions: Existing SRNS prediction models reported apparent discrimination but had a high risk of bias and very limited external validation, which substantially restricts their current clinical applicability. Several relevant risk factors remain unincorporated. Future research should prioritize rigorous model development and multi-center external validation.
Keywords: nephrotic syndrome; prediction model; risk factor; steroid resistance nephrotic syndrome; prediction model; risk factor; steroid resistance
Graphical Abstract

Share and Cite

MDPI and ACS Style

Hu, Y.; Zhang, Z.; Diao, S.; Guo, Y.; Gao, Y.; Xu, Z.; Peng, Q.; Xu, Y.; Bo, Z.; Zeng, L.; et al. Prediction Models and Risk Factors for Steroid Resistance in Children with Nephrotic Syndrome: A Systematic Review and Meta-Analysis. J. Clin. Med. 2026, 15, 4438. https://doi.org/10.3390/jcm15124438

AMA Style

Hu Y, Zhang Z, Diao S, Guo Y, Gao Y, Xu Z, Peng Q, Xu Y, Bo Z, Zeng L, et al. Prediction Models and Risk Factors for Steroid Resistance in Children with Nephrotic Syndrome: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine. 2026; 15(12):4438. https://doi.org/10.3390/jcm15124438

Chicago/Turabian Style

Hu, Yuanhui, Zehui Zhang, Sha Diao, Yannan Guo, Yangtingting Gao, Zheng Xu, Qilin Peng, Yao Xu, Zhenyan Bo, Linan Zeng, and et al. 2026. "Prediction Models and Risk Factors for Steroid Resistance in Children with Nephrotic Syndrome: A Systematic Review and Meta-Analysis" Journal of Clinical Medicine 15, no. 12: 4438. https://doi.org/10.3390/jcm15124438

APA Style

Hu, Y., Zhang, Z., Diao, S., Guo, Y., Gao, Y., Xu, Z., Peng, Q., Xu, Y., Bo, Z., Zeng, L., Huang, L., Chen, J., Zhu, Y., Li, H., & Zhang, L. (2026). Prediction Models and Risk Factors for Steroid Resistance in Children with Nephrotic Syndrome: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine, 15(12), 4438. https://doi.org/10.3390/jcm15124438

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop