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A Novel Nomogram for Predicting Gonadotropin-Releasing Hormone Analogue Treatment Outcome in Girls with Idiopathic
Shiyi Xu1, Limei Guan1,2, Qiuting Lin1
1College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350000, People's Republic of China.
Objective:
To explore the nomogram prediction model of long-acting gonadotropin-releasing hormone analogue (GnRHa) based on the clinical characteristics, bone metabolism and ovarian function of girls with idiopathic central precocious puberty (ICPP) and its clinical application value.
Methods:
A total of 134 girls with ICPP who received long-term GnRHa treatment at our hospital from May 2021 to February 2024 were selected and randomly divided into a training set (n=94) and a validation set (n=40) in a 7:3 ratio. In the training set, univariate analysis and multivariate logistic regression analyses were used to identify factors influencing treatment efficacy, based on which a nomogram prediction model was constructed. The model's predictive performance was evaluated using the receiver operating characteristic (ROC) curve and calibration curve, while its clinical application value was assessed by decision curve analysis (DCA).
Results:
In the training set, 18 out of 94 children (19.15%) had a poor treatment response, compared to 7 out of 40 children (17.50%) in the validation set. Multivariate regression analysis showed that the higher degree of breast development, more pubic hair growth, higher level of N-MID, higher level of ALP, larger ovarian volume, more follicles, and higher levels of LH, FSH and E2 were the independent risk factors for poor curative effect of GnRHa (all P<0.05). The constructed nomogram demonstrated good predictive performance in both sets: the area under the ROC curve (AUC) was 0.870 (95% CI: 0.814-0.927) in the training set and 0.810 (95% CI: 0.711-0.909) in the validation set. Calibration curves showed good agreement between predicted and observed outcomes. DCA indicated that the model provided net clinical benefit across a wide threshold probability range (approximately 0.1-0.8).
Conclusion:
Based on the clinical characteristics, bone metabolism and ovarian function of girls with idiopathic central precocious puberty, the nomogram prediction model of long-acting gonadotropin-releasing hormone analogues is helpful to predict the curative effect of GnRHa at an early stage, guide clinical decision-making and optimize the treatment plan.
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