Nomogram prediction model construction for rapidly progressing-idiopathic central precocious puberty in girls
Shu Qiaozhi, Weng Lijuan , Pei Chuanfeng, et al
(1. Department of Pediatric Outpatient and Emergency, Shanghai General Hospital, Shanghai 201620, China; 2. Department of Gynecology, Shanghai General Hospital, Shanghai 201620, China)
Abstract: 【Abstract】 Objective To construct a rapid progression warning model for idiopathic central precocious puberty (ICPP) in girls based on uterine and ovarian ultrasound examinations and laboratory test indicators, and validate its clinical application value, aiming to provide a reference for clinical screening of high-risk rapidly progressive-ICPP (RP-ICPP) in girls. Method A total of 200 girls with newly diagnosed ICPP at Department of Pediatric Outpatient and Emergency, Shanghai General Hospital from March 2020 to March 2022 were selected by a prospective study, and they were randomly divided into the training set (n=140) and the test set (n=60) at a ratio of 7∶3. The incidence of RP-ICPP after 6-month follow-up without intervention in training set and test set was calculated, and patients were divided into the RP-ICPP group and the non-RPICPP group. The general information, ultrasound indicators of uterus and ovary, and laboratory test indicators at admission were compared between the RP-ICPP group and the non-RP-ICPP group in training set and test set. In the training set, factors influencing RP-ICPP were analyzed, and a prediction model for RP-ICPP was constructed, the model was verified respectively in the training set and test set. Statistical analysis performed by t-test and χ2 test. Multivariate Logistic regression analysis was used to evaluate the influencing factors of RP-ICPP, and a Nomogram prediction model of RP-ICPP was constructed. The predictive efficacy, calibration degree and clinical utility of the model were evaluated by using the calibration curve and decision curve. Result The incidence rates of RP-ICPP in girls with newly diagnosed ICPP in the training set and test set after a 6-month follow-up without intervention were 55.71% (78/140) and 56.67% (34/60), respectively. In the training set, the RP-ICPP group showed higher values than the non-RP-ICPP group in the following parameters: initial bone age minus chronological age (BA0-CA0), uterine volume, ovarian volume, basal levels of luteinizing hormone (LH), basal levels of follicle-stimulating hormone (FSH), inhibin B (INHB), insulin-like growth factor-1 (IGF-1), dehydroepiandrosterone sulfate (DHEAS), and the proportion of vitamin D deficiency, the differences were all statistically significant (all P<0.05). In the test set, the BA0-CA0, uterine volume, ovarian volume, basal levels of LH, basal levels of FSH, INHB, IGF-1, DHEAS and the proportion of vitamin D deficiency in the RP-ICPP group were all higher than those in the non-RP-ICPP group, and the differences were statistically significant (all P<0.05). The results of multivariate Logistic regression analysis showed that BA0-CA0, uterine volume, ovarian volume, basal levels of LH, basal levels of FSH, INHB, IGF-1, DHEAS (all as continuous variables), and vitamin D (normal=0, deficiency=1) were all influencing factors for RP-ICPP (all P<0.05). Based on the forest plot of RP-ICPP influencing factors in the training set, BA0-CA0, uterine volume, ovarian volume, basal levels of LH, basal levels of FSH, INHB, IGF-1, DHEAS, and vitamin D deficiency were all positively correlated risk factors for the occurrence of RPICPP in girls with newly diagnosed ICPP (all P<0.05). The Nomogram prediction model demonstrated good discriminative ability, with C-indexes of 0.851 and 0.843 in the training set and test set, respectively, and exhibited favorable calibration and clinical utility in predicting the occurrence of RP-ICPP in girls with newly diagnosed ICPP. Conclusion The Nomogram prediction model constructed based on uterine and ovarian ultrasound examinations and laboratory test indicators demonstrates good predictive value for RP-ICPP.
舒侨芝 翁丽娟 裴传凤 徐喜艳 张英丽. 女童特发性中枢性性早熟病情快速进展的Nomogram 预测模型构建[J]. 发育医学电子杂志, 2025, 13(4): 252-260.
Shu Qiaozhi, Weng Lijuan , Pei Chuanfeng, et al. Nomogram prediction model construction for rapidly progressing-idiopathic central precocious puberty in girls. Journal of Developmental Medicine(Electronic Version), 2025, 13(4): 252-260.
2025, Vol. 13 
