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Clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study

BACKGROUND: The gold standard for the diagnosis of central precocious puberty (CPP) is gonadotropin-releasing hormone (GnRH) or GnRH analogs (GnRHa) stimulation test. But the stimulation test is time-consuming and costly. Our objective was to develop a risk score model readily adoptable by clinician...

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Autores principales: You, Jingyu, Cheng, Xianying, Li, Xiaojing, Li, Mingqing, Yao, Li, Luo, Feihong, Cheng, Ruoqian, Xi, Li, Ye, Jiangfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056580/
https://www.ncbi.nlm.nih.gov/pubmed/33879124
http://dx.doi.org/10.1186/s12902-021-00740-7
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author You, Jingyu
Cheng, Xianying
Li, Xiaojing
Li, Mingqing
Yao, Li
Luo, Feihong
Cheng, Ruoqian
Xi, Li
Ye, Jiangfeng
author_facet You, Jingyu
Cheng, Xianying
Li, Xiaojing
Li, Mingqing
Yao, Li
Luo, Feihong
Cheng, Ruoqian
Xi, Li
Ye, Jiangfeng
author_sort You, Jingyu
collection PubMed
description BACKGROUND: The gold standard for the diagnosis of central precocious puberty (CPP) is gonadotropin-releasing hormone (GnRH) or GnRH analogs (GnRHa) stimulation test. But the stimulation test is time-consuming and costly. Our objective was to develop a risk score model readily adoptable by clinicians and patients. METHODS: A cross-sectional study based on the electronic medical record system was conducted in the Children’s Hospital, Fudan University, Shanghai, China from January 2010 to August 2016. Patients with precocious puberty were randomly split into the training (n = 314) and validation (n = 313) sample. In the training sample, variables associated with CPP (P < 0.2) in univariate analyses were introduced in a multivariable logistic regression model. Prediction model was selected using a forward stepwise analysis. A risk score model was built with the scaled coefficients of the model and tested in the validation sample. RESULTS: CPP was diagnosed in 54.8% (172/314) and 55.0% (172/313) of patients in the training and validation sample, respectively. The CPP risk score model included age at the onset of puberty, basal luteinizing hormone (LH) concentration, largest ovarian volume, and uterine volume. The C-index was 0.85 (95% CI: 0.81–0.89) and 0.86 (95% CI: 0.82–0.90) in the training and the validation sample, respectively. Two cut-off points were selected to delimitate a low- (< 10 points), median- (10–19 points), and high-risk (≥ 20 points) group. CONCLUSIONS: A risk score model for the risk of CPP had a moderate predictive performance, which offers the advantage of helping evaluate the requirement for further diagnostic tests (GnRH or GnRHa stimulation test). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12902-021-00740-7.
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spelling pubmed-80565802021-04-20 Clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study You, Jingyu Cheng, Xianying Li, Xiaojing Li, Mingqing Yao, Li Luo, Feihong Cheng, Ruoqian Xi, Li Ye, Jiangfeng BMC Endocr Disord Research Article BACKGROUND: The gold standard for the diagnosis of central precocious puberty (CPP) is gonadotropin-releasing hormone (GnRH) or GnRH analogs (GnRHa) stimulation test. But the stimulation test is time-consuming and costly. Our objective was to develop a risk score model readily adoptable by clinicians and patients. METHODS: A cross-sectional study based on the electronic medical record system was conducted in the Children’s Hospital, Fudan University, Shanghai, China from January 2010 to August 2016. Patients with precocious puberty were randomly split into the training (n = 314) and validation (n = 313) sample. In the training sample, variables associated with CPP (P < 0.2) in univariate analyses were introduced in a multivariable logistic regression model. Prediction model was selected using a forward stepwise analysis. A risk score model was built with the scaled coefficients of the model and tested in the validation sample. RESULTS: CPP was diagnosed in 54.8% (172/314) and 55.0% (172/313) of patients in the training and validation sample, respectively. The CPP risk score model included age at the onset of puberty, basal luteinizing hormone (LH) concentration, largest ovarian volume, and uterine volume. The C-index was 0.85 (95% CI: 0.81–0.89) and 0.86 (95% CI: 0.82–0.90) in the training and the validation sample, respectively. Two cut-off points were selected to delimitate a low- (< 10 points), median- (10–19 points), and high-risk (≥ 20 points) group. CONCLUSIONS: A risk score model for the risk of CPP had a moderate predictive performance, which offers the advantage of helping evaluate the requirement for further diagnostic tests (GnRH or GnRHa stimulation test). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12902-021-00740-7. BioMed Central 2021-04-20 /pmc/articles/PMC8056580/ /pubmed/33879124 http://dx.doi.org/10.1186/s12902-021-00740-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
You, Jingyu
Cheng, Xianying
Li, Xiaojing
Li, Mingqing
Yao, Li
Luo, Feihong
Cheng, Ruoqian
Xi, Li
Ye, Jiangfeng
Clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study
title Clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study
title_full Clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study
title_fullStr Clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study
title_full_unstemmed Clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study
title_short Clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study
title_sort clinical risk score for central precocious puberty among girls with precocious pubertal development: a cross sectional study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056580/
https://www.ncbi.nlm.nih.gov/pubmed/33879124
http://dx.doi.org/10.1186/s12902-021-00740-7
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