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Development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia
Microdissection testicular sperm extraction (micro-TESE) is widely used to treat nonobstructive azoospermia. However, a good prediction model is required to anticipate a successful sperm retrieval rate before performing micro-TESE. This retrospective study analyzed the clinical records of 200 nonobs...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521962/ https://www.ncbi.nlm.nih.gov/pubmed/36814170 http://dx.doi.org/10.4103/aja2022111 |
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author | Deng, Chen-Yao Liu, De-Feng Zhao, Lian-Ming Lin, Hao-Cheng Mao, Jia-Ming Zhang, Zhe Yang, Yu-Zhuo Zhang, Hai-Tao Hong, Kai Xu, Hui-Yu Jiang, Hui |
author_facet | Deng, Chen-Yao Liu, De-Feng Zhao, Lian-Ming Lin, Hao-Cheng Mao, Jia-Ming Zhang, Zhe Yang, Yu-Zhuo Zhang, Hai-Tao Hong, Kai Xu, Hui-Yu Jiang, Hui |
author_sort | Deng, Chen-Yao |
collection | PubMed |
description | Microdissection testicular sperm extraction (micro-TESE) is widely used to treat nonobstructive azoospermia. However, a good prediction model is required to anticipate a successful sperm retrieval rate before performing micro-TESE. This retrospective study analyzed the clinical records of 200 nonobstructive azoospermia patients between January 2021 and December 2021. The backward method was used to perform binary logistic regression analysis and identify factors that predicted a successful micro-TESE sperm retrieval. The prediction model was constructed using acquired regression coefficients, and its predictive performance was assessed using the receiver operating characteristic curve. In all, 67 patients (sperm retrieval rate: 33.5%) underwent successful micro-TESE. Follicle-stimulating hormone, anti-Müllerian hormone, and inhibin B levels varied significantly between patients who underwent successful and unsuccessful micro-TESE. Binary logistic regression analysis yielded the following six predictors: anti-Müllerian hormone (odds ratio [OR] = 0.902, 95% confidence interval [CI]: 0.821–0.990), inhibin B (OR = 1.012, 95% CI: 1.001–1.024), Klinefelter’s syndrome (OR = 0.022, 95% CI: 0.002–0.243), Y chromosome microdeletion (OR = 0.050, 95% CI: 0.005–0.504), cryptorchidism with orchiopexy (OR = 0.085, 95% CI: 0.008–0.929), and idiopathic nonobstructive azoospermia (OR = 0.031, 95% CI: 0.003–0.277). The prediction model had an area under the curve of 0.720 (95% CI: 0.645–0.794), sensitivity of 65.7%, specificity of 72.2%, Youden index of 0.379, and cut-off value of 0.305 overall, indicating good predictive value and accuracy. This model can assist clinicians and nonobstructive azoospermia patients in decision-making and avoiding negative micro-TESE results. |
format | Online Article Text |
id | pubmed-10521962 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-105219622023-09-27 Development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia Deng, Chen-Yao Liu, De-Feng Zhao, Lian-Ming Lin, Hao-Cheng Mao, Jia-Ming Zhang, Zhe Yang, Yu-Zhuo Zhang, Hai-Tao Hong, Kai Xu, Hui-Yu Jiang, Hui Asian J Androl Original Article Microdissection testicular sperm extraction (micro-TESE) is widely used to treat nonobstructive azoospermia. However, a good prediction model is required to anticipate a successful sperm retrieval rate before performing micro-TESE. This retrospective study analyzed the clinical records of 200 nonobstructive azoospermia patients between January 2021 and December 2021. The backward method was used to perform binary logistic regression analysis and identify factors that predicted a successful micro-TESE sperm retrieval. The prediction model was constructed using acquired regression coefficients, and its predictive performance was assessed using the receiver operating characteristic curve. In all, 67 patients (sperm retrieval rate: 33.5%) underwent successful micro-TESE. Follicle-stimulating hormone, anti-Müllerian hormone, and inhibin B levels varied significantly between patients who underwent successful and unsuccessful micro-TESE. Binary logistic regression analysis yielded the following six predictors: anti-Müllerian hormone (odds ratio [OR] = 0.902, 95% confidence interval [CI]: 0.821–0.990), inhibin B (OR = 1.012, 95% CI: 1.001–1.024), Klinefelter’s syndrome (OR = 0.022, 95% CI: 0.002–0.243), Y chromosome microdeletion (OR = 0.050, 95% CI: 0.005–0.504), cryptorchidism with orchiopexy (OR = 0.085, 95% CI: 0.008–0.929), and idiopathic nonobstructive azoospermia (OR = 0.031, 95% CI: 0.003–0.277). The prediction model had an area under the curve of 0.720 (95% CI: 0.645–0.794), sensitivity of 65.7%, specificity of 72.2%, Youden index of 0.379, and cut-off value of 0.305 overall, indicating good predictive value and accuracy. This model can assist clinicians and nonobstructive azoospermia patients in decision-making and avoiding negative micro-TESE results. Wolters Kluwer - Medknow 2023-02-07 /pmc/articles/PMC10521962/ /pubmed/36814170 http://dx.doi.org/10.4103/aja2022111 Text en Copyright: © The Author(s)(2023) https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Deng, Chen-Yao Liu, De-Feng Zhao, Lian-Ming Lin, Hao-Cheng Mao, Jia-Ming Zhang, Zhe Yang, Yu-Zhuo Zhang, Hai-Tao Hong, Kai Xu, Hui-Yu Jiang, Hui Development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia |
title | Development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia |
title_full | Development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia |
title_fullStr | Development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia |
title_full_unstemmed | Development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia |
title_short | Development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia |
title_sort | development of a predictive model for increasing sperm retrieval success by microdissection testicular sperm extraction in patients with nonobstructive azoospermia |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521962/ https://www.ncbi.nlm.nih.gov/pubmed/36814170 http://dx.doi.org/10.4103/aja2022111 |
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