已发表论文

儿童身材矮小生长激素缺乏临床预测模型的开发与验证:一项中国回顾性研究

 

Authors Li M, Liu C, Yang Y, Hu S, Li J, Qiu S, Wang Z

Received 16 April 2025

Accepted for publication 1 August 2025

Published 5 September 2025 Volume 2025:18 Pages 5551—5561

DOI https://doi.org/10.2147/JMDH.S534760

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr David C. Mohr

Mali Li, Chao Liu, Yuan Yang, Shuwen Hu, Jia Li, Shichao Qiu, Zhihua Wang

Department of Endocrinology, Genetics and Metabolism, Xi’an Children’s Hospital, Xi’an, Shaanxi, People’s Republic of China

Correspondence: Zhihua Wang, Department of Endocrinology, Genetics and Metabolism, Xi’an Children’s Hospital, Xi’an, Shaanxi, People’s Republic of China, Email xasetyy@126.com

Background: A multitude of congenital and acquired conditions can result in short stature, each with distinctive clinical presentations and treatment options. We aimed to develop and validate a prediction model to identify GHD among children with short stature using clinical and laboratory parameters.
Methods: This retrospective observational study included 1120 children with short stature from a hospital in China. The data were randomly split into a derivation set and a validation set. Features were selected based on clinical relevance and statistical significance to construct a multivariate logistic regression model in the derivation set. Discrimination, calibration, and prediction accuracy were evaluated on both sets.
Results: Of the 1120 children, 278 (25%) were diagnosed with GHD, 694 (62%) were male, and the mean age was 6.97 ± 2.97 years. The derivation set comprises 785 (70%) children. The model incorporates four predictors: age (OR=0.761; 95% CI 0.660, 0.873), delayed bone age (OR=1.841; 95% CI 1.365, 2.537), IGF-1 SDS (OR=0.148; 95% CI 0.095, 0.220), and IGF-1/IGFBP-3 ratio (OR=0.901; 95% CI 0.870, 0.930). The model exhibits good discriminative ability, with an AUC of 0.952 (0.937, 0.967) in the derivation set and 0.950 (0.927, 0.973) in the validation set. Furthermore, it shows high accuracy with sensitivity and specificity of 0.895 in the derivation set, which was 0.946 and 0.851 in the validation set. The model also demonstrates reliable calibration.
Conclusion: We have developed a prediction model for accurate screening of GHD in children with short stature.

Keywords: growth hormone deficiency, short stature, prediction model, insulin-like growth factor 1, insulin-like growth factor binding protein 3, bone age