AUTHOR=Yang Xin , Jiang Hui , Liao Min , Lin Meng , Wu Jin 

TITLE=Construction of a nomogram for predicting serum vitamin D deficiency in children/adolescents with new-onset type 1 diabetes: a single-center study in China

JOURNAL=Frontiers in Pediatrics

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2025.1554833

DOI=10.3389/fped.2025.1554833

ISSN=2296-2360

ABSTRACT=ObjectiveThe vitamin D–type 1 diabetes (T1D) association has been debated in public health. The purpose of this study was to develop a vitamin D deficiency prediction model and investigate vitamin D deficiency risk factors in children and adolescents with new-onset T1D.MethodsA single-centre, retrospective analysis of paediatric patients (1–18 years) with new-onset T1D and initial 25-hydroxyvitamin D assessments was performed at a tertiary hospital in China between January 2020 and July 2024 (n = 353). The patients were divided into two groups according to whether their vitamin D deficiency exceeded 12 ng/ml. After identifying vitamin D deficiency risk factors in children/adolescents with new-onset T1D, a receiver operating characteristic (ROC) curve model was developed to predict the probability of vitamin D deficiency in these individuals. That model was represented with a nomogram. Calibration and clinical decision analysis curves were used to evaluate the model's effectiveness after internal validation via bootstrapping.ResultsThe prevalence rate of serum vitamin D deficiency among patients with new-onset T1D was 26.35% (93/353). Multivariate logistic regression analysis revealed that minority status (X1), weight (X2), diabetic ketoacidosis severity (X3), serum vitamin D testing season (X4), free triiodothyronine (X5), and high-density lipoprotein (X6) were closely associated with serum vitamin D deficiency development in children/adolescents with new-onset T1D (P < 0.05). The model was logit (P) =ex/(1 + ex), X = 4.626−1.878*X1−0.038*X2−0.821*X3−0.88*X4 + 0.351*X5 + 0.532*X6. The area under the curve (AUC) of the serum vitamin D deficiency predictive model among patients with new-onset T1D was 0.769 (95% CI = 0.711–0.826). The predicted probability's best cut-off value was 0.671.ConclusionsThe established risk prediction model has good efficacy, providing a reference for screening high-risk vitamin D deficiency groups among children/adolescents with new-onset T1D and taking preventive and protective measures. The nomogram was developed based on a single-center cohort in China, and its generalizability needs further validation in more extensive populations.