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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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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. |
format | Online Article Text |
id | pubmed-8056580 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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