Performance of adult height prediction methods in 6 to 8-year-old girls with GnRH-dependent precocious puberty
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Anni Erkko
Abstract
Objectives
In girls with precocious puberty (PP), adult height prediction (PAH) is crucial in treatment planning, yet the estimations may be prone to inaccuracies. This study aimed to compare the accuracy of two commonly used PAH methods in 6–8-year-old girls diagnosed with idiopathic GnRH-dependent PP.
Methods
This retrospective study included data on 60 six- to eight-year-old girls diagnosed with PP. Data was collected from medical records. Forty-eight (82 %) girls were treated with GnRH analogues, and 18 (30 %) had data on AH. Bone ages (BA) were assessed with Greulich–Pyle and BoneXpert. PAHs were estimated with Bayley-Pinneau and BoneXpert.
Results
In girls treated with GnRH-analogue, AH did not significantly differ from the mean PAH calculated by Bayley-Pinneau (mean difference, −0.1 cm ± 6.6 cm (SD); p=0.93). Predicted adult height estimated by BoneXpert was higher than the actual AH (−3.6 cm ± 4.6 cm, p=0.01), but it showed lower variability in individual prediction errors and less bias related to the degree of BA advancement than Bayley-Pinneau. All subjects reached their mid-parental target height range.
Conclusions
In 6- to 8-year-old girls with signs of idiopathic GnRH-dependent precocious puberty, the potential to reach their growth target remains, and overestimation of residual height growth at diagnosis should be carefully considered before initiating treatment.
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Research ethics: This study was approved by the HUH, the ethics committee for gynecology and obstetrics, pediatrics, and psychiatry of HUH and declaration of Helsinki was followed.
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Author contributions: TV, A-PI, JK, KW, KV were included in acquired and analyzed the data, and participated in the manuscript drafting. MH, PJM did the critical analysis of the manuscript. MN, TR made the concept and design of the study, and drafted and critically analyzed the manuscript. All authors approved the final version of the manuscript.
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Use of Large Language Models, AI and Machine Learning Tools: Open AI was used to improve language in abstract.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: This work was supported by the Foundation for Pediatric Research, Sigrid Juselius Foundation, the Academy of Finland, and Helsinki University Hospital Research Funds.
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Data availability: The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
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