Central precocious puberty risk prediction model for Chinese children: a cross-sectional study

Abstract Objective The aim of this study was to explore the risk factors of central precocious puberty (CPP) in children, furthermore, develop and evaluate the risk prediction model in CPP children.Methods A cross-sectional study based on the electronic medical record system was conducted in the Children Health Care Center in a tertiary A-level hospital in China. A total of 187 children agreed to participate the study from August 2020 to July 2021. Children were split into the central precocious puberty group (n=52) and non-precocious puberty group (n=135), the collected variables associated with CPP (P<0.05) in univariate analyses were introduced in logistic regression analysis to construct the risk prediction model. Then a nomogram was built to visualize the model, and the receiver operating characteristic (ROC) curve was used to predictive the effect of the model.Results The risk factors of CPP children in the risk prediction model were bodyweight (OR=2.383), entertainment time for electronic devices (OR=0.042), sweet tooth (OR=12.400), fried food lover (OR=8.696), and intake of carbonated soft drinks (OR=15.816). The area under the ROC curve (AUC) was 0.874 (95% CI: 0.817-0.931), the sensitivity was 0.852, the specificity was 0.769, the Youden index was 0.621, and the optimum critical value was 0.960. Conclusions The nomogram risk prediction model can effectively predict the CPP occurrence in children and provide references for clinical evaluation and early intervention.