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Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol

OBJECTIVE: To explore the relative factors for best ovarian response in patients undergoing assisted reproductive technology with the gonadotropin-releasing hormone antagonist protocol and to establish a nomogram prediction model of ovarian response. METHODS: A retrospective cohort analysis of the c...

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Autores principales: Jiang, Wenwen, Zheng, Beihong, Liao, Xiuhua, Chen, Xiaojing, Zhu, Suqin, Li, Rongshan, Zhang, Huale
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9705959/
https://www.ncbi.nlm.nih.gov/pubmed/36457552
http://dx.doi.org/10.3389/fendo.2022.1030201
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author Jiang, Wenwen
Zheng, Beihong
Liao, Xiuhua
Chen, Xiaojing
Zhu, Suqin
Li, Rongshan
Zhang, Huale
author_facet Jiang, Wenwen
Zheng, Beihong
Liao, Xiuhua
Chen, Xiaojing
Zhu, Suqin
Li, Rongshan
Zhang, Huale
author_sort Jiang, Wenwen
collection PubMed
description OBJECTIVE: To explore the relative factors for best ovarian response in patients undergoing assisted reproductive technology with the gonadotropin-releasing hormone antagonist protocol and to establish a nomogram prediction model of ovarian response. METHODS: A retrospective cohort analysis of the clinical data of 1,944 patients who received assisted reproductive treatment in the Center for Reproductive Medicine of Fujian Maternity and Child Health Hospital from April 1, 2018, to June 30, 2020. According to the number of oocytes obtained, there were 659 cases in the low ovarian response group (no more than five oocytes were retrieved), 920 cases in the normal ovarian response group (the number of retrieved oocytes was >5 but ≤18), and 365 cases in the high ovarian response group (>18 oocytes retrieved). Independent factors affecting ovarian responsiveness were screened by logistic regression, which were the model entry variables, and a nomogram prediction model was established based on the regression coefficients. RESULTS: There were statistically significant differences in age, anti-Mullerian hormone, antral follicle count, the diagnosis of endometriosis, decreased ovarian reserve, polycystic ovary syndrome, basal follicle-stimulating hormone and basal luteinizing hormone among the three groups (P < 0.001). Multifactorial stepwise regression analysis showed that female age (0.95 [0.92–0.97], P = 0.000), decreased ovarian reserve (0.27 [0.19-0.38]), P = 0.000), endometriosis (0.81 [0.56-0.86], P = 0.000), antral follicle count (1.09 [1.06-1.12], P = 0.000), basal follicle-stimulating hormone (0.90 [0.85-0.96], P = 0.001), Anti-Mullerian hormone (1.19 [1.13–1.26], P= 0.000) and luteinizing hormone on trigger day (0.73 [0.66–0.80], P= 0.000), were independent factors for the occurrence of different ovarian responses during ovarian hyperstimulation. The predictive model of ovarian responsiveness was constructed based on the above factors, and the model was verified with 589 patients’ data from July 1, 2020, to December 31, 2020, at this center. The predicted ovarian response (number of eggs obtained) of a total of 450 patients was consistent with the actual results, with a coincidence degree of 76.4%, and the consistency index of the model is 0.77. CONCLUSION: The nomogram model was successfully developed to effectively, intuitively, and visually predict the ovary reactivity in the gonadotropin-releasing hormone antagonist protocol and provide guidance for clinical practice.
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spelling pubmed-97059592022-11-30 Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol Jiang, Wenwen Zheng, Beihong Liao, Xiuhua Chen, Xiaojing Zhu, Suqin Li, Rongshan Zhang, Huale Front Endocrinol (Lausanne) Endocrinology OBJECTIVE: To explore the relative factors for best ovarian response in patients undergoing assisted reproductive technology with the gonadotropin-releasing hormone antagonist protocol and to establish a nomogram prediction model of ovarian response. METHODS: A retrospective cohort analysis of the clinical data of 1,944 patients who received assisted reproductive treatment in the Center for Reproductive Medicine of Fujian Maternity and Child Health Hospital from April 1, 2018, to June 30, 2020. According to the number of oocytes obtained, there were 659 cases in the low ovarian response group (no more than five oocytes were retrieved), 920 cases in the normal ovarian response group (the number of retrieved oocytes was >5 but ≤18), and 365 cases in the high ovarian response group (>18 oocytes retrieved). Independent factors affecting ovarian responsiveness were screened by logistic regression, which were the model entry variables, and a nomogram prediction model was established based on the regression coefficients. RESULTS: There were statistically significant differences in age, anti-Mullerian hormone, antral follicle count, the diagnosis of endometriosis, decreased ovarian reserve, polycystic ovary syndrome, basal follicle-stimulating hormone and basal luteinizing hormone among the three groups (P < 0.001). Multifactorial stepwise regression analysis showed that female age (0.95 [0.92–0.97], P = 0.000), decreased ovarian reserve (0.27 [0.19-0.38]), P = 0.000), endometriosis (0.81 [0.56-0.86], P = 0.000), antral follicle count (1.09 [1.06-1.12], P = 0.000), basal follicle-stimulating hormone (0.90 [0.85-0.96], P = 0.001), Anti-Mullerian hormone (1.19 [1.13–1.26], P= 0.000) and luteinizing hormone on trigger day (0.73 [0.66–0.80], P= 0.000), were independent factors for the occurrence of different ovarian responses during ovarian hyperstimulation. The predictive model of ovarian responsiveness was constructed based on the above factors, and the model was verified with 589 patients’ data from July 1, 2020, to December 31, 2020, at this center. The predicted ovarian response (number of eggs obtained) of a total of 450 patients was consistent with the actual results, with a coincidence degree of 76.4%, and the consistency index of the model is 0.77. CONCLUSION: The nomogram model was successfully developed to effectively, intuitively, and visually predict the ovary reactivity in the gonadotropin-releasing hormone antagonist protocol and provide guidance for clinical practice. Frontiers Media S.A. 2022-11-15 /pmc/articles/PMC9705959/ /pubmed/36457552 http://dx.doi.org/10.3389/fendo.2022.1030201 Text en Copyright © 2022 Jiang, Zheng, Liao, Chen, Zhu, Li and Zhang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Jiang, Wenwen
Zheng, Beihong
Liao, Xiuhua
Chen, Xiaojing
Zhu, Suqin
Li, Rongshan
Zhang, Huale
Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol
title Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol
title_full Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol
title_fullStr Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol
title_full_unstemmed Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol
title_short Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol
title_sort analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9705959/
https://www.ncbi.nlm.nih.gov/pubmed/36457552
http://dx.doi.org/10.3389/fendo.2022.1030201
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