A Novel Nomogram for Predicting Gonadotropin-Releasing Hormone Analogue Treatment Outcome in Girls with Idiopathic Central Precocious Puberty

The study developed a nomogram prediction model to assess the treatment outcome of long-acting gonadotropin-releasing hormone analogue (GnRHa) in 134 girls with idiopathic central precocious puberty (ICPP). The model was based on clinical characteristics, bone metabolism, and ovarian function. Key risk factors for poor treatment response included advanced breast development, pubic hair growth, and elevated levels of N-MID, ALP, LH, FSH, and E2. The model showed strong predictive performance with an AUC of 0.870 in the training set and 0.810 in the validation set. It demonstrated good calibration and provided clinical benefits across a wide probability range, aiding in early prediction of treatment efficacy and guiding clinical decisions.