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

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.