ArticleInternational journal of women's health2026
A Novel Nomogram for Predicting Gonadotropin-Releasing Hormone Analogue Treatment Outcome in Girls with Idiopathic Central Precocious Puberty.
Article in International journal of women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.