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Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer
PURPOSE: To construct and validate a nomogram model for predicting clinical pregnancy in individuals with endometriosis undergoing fersh embryo transfer (ET). METHODS: A retrospective analysis was conducted on 1630 individuals with endometriosis who underwent in vitro fertilization (IVF) with fresh...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10617063/ https://www.ncbi.nlm.nih.gov/pubmed/37907870 http://dx.doi.org/10.1186/s12884-023-06082-7 |
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author | Zhu, Suqin Liao, Xiuhua Jiang, Wenwen Sun, Yan Chen, Xiaojing Zheng, Beihong |
author_facet | Zhu, Suqin Liao, Xiuhua Jiang, Wenwen Sun, Yan Chen, Xiaojing Zheng, Beihong |
author_sort | Zhu, Suqin |
collection | PubMed |
description | PURPOSE: To construct and validate a nomogram model for predicting clinical pregnancy in individuals with endometriosis undergoing fersh embryo transfer (ET). METHODS: A retrospective analysis was conducted on 1630 individuals with endometriosis who underwent in vitro fertilization (IVF) with fresh embryo transfer at the Reproductive Medicine Center of Fujian Maternity and Child Health Hospital from January 2018 to January 2022. The research population was sorted into two groups through random sampling, namely, the model group (n = 1141) and the validation group (n = 489), with a ratio of 7:3. Univariate analysis was utilized to determine the influencing factors for clinical pregnancy in the model group. The LASSO algorithm was utilized to select the optimal matching factors, which were then included in a multifactorial forward stepwise logistic regression to determine independent influencing factors and develop a nomogram. The discrimination, accuracy, and clinical efficacy of the prediction model were analyzed utilizing the receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve. RESULTS: Through multivariate-logistic-regression analysis, these factors were identified as independent influencing factors for the clinical pregnancy in endometriosis patients undergoing fresh embryo transfer: female age (OR = 0.933, 95% CI = 0.902–0.965, P < 0.001), ASRM stage (OR = 0.384, 95% CI = 0.276–0.532, P < 0.001), postoperative to IVF duration (OR = 0.496, 95% CI = 0.356–0.688, P < 0.001), antral follicle count (AFC) (OR = 1.076, 95% CI = 1.013–1.161, P = 0.045), anti-Müllerian hormone (AMH) (OR = 1.202, 95% CI = 1.073–1.35, P = 0.002), Gonadotrophin-releasing hormone (GnRH) agonist protocol (OR = 1.536, 95% CI = 1.109–2.131, P = 0.01), number of oocytes retrieved (OR = 1.154, 95% CI = 1.067–1.249, P < 0.001), number of high-quality cleavage embryos (OR = 1.261, 95% CI = 1.164–1.369, P < 0.001), and number of embryos transferred (OR = 1.957, 95% CI = 1.435–2.679, P < 0.001). A prediction model for estimating the clinical pregnancy probability in individuals with endometriosis was constructed per these identified independent factors. The ROC showed an area under the curve (AUC) of 0.807 (95% CI = 0.782–0.832) in the model group and 0.800 (95% CI = 0.761–0.84) in the validation group. The Hosmer-Lemeshow test demonstrated no statistically significant difference between predicted and actual clinical pregnancy probabilities (P > 0.05). The clinical decision curve demonstrated that both the model and the validation groups achieved maximum net benefit at threshold probability values of 0.08–0.96 and 0.16–0.96, indicating good clinical efficacy within this range of threshold probabilities. CONCLUSION: Female age, ASRM stage, postoperative to IVF duration, stimulation protocol, AFC, AMH, number of oocytes retrieved, number of high-quality cleavage embryos and number of transferred embryos are independent influencing factors for the clinical pregnancy rate in individuals with endometriosis receiving fresh embryo transfer. The nomogram model based on these factors demonstrates good clinical predictive value and efficacy, providing a basis for clinical prognosis, intervention, and individualized medical treatment planning. |
format | Online Article Text |
id | pubmed-10617063 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106170632023-11-01 Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer Zhu, Suqin Liao, Xiuhua Jiang, Wenwen Sun, Yan Chen, Xiaojing Zheng, Beihong BMC Pregnancy Childbirth Research PURPOSE: To construct and validate a nomogram model for predicting clinical pregnancy in individuals with endometriosis undergoing fersh embryo transfer (ET). METHODS: A retrospective analysis was conducted on 1630 individuals with endometriosis who underwent in vitro fertilization (IVF) with fresh embryo transfer at the Reproductive Medicine Center of Fujian Maternity and Child Health Hospital from January 2018 to January 2022. The research population was sorted into two groups through random sampling, namely, the model group (n = 1141) and the validation group (n = 489), with a ratio of 7:3. Univariate analysis was utilized to determine the influencing factors for clinical pregnancy in the model group. The LASSO algorithm was utilized to select the optimal matching factors, which were then included in a multifactorial forward stepwise logistic regression to determine independent influencing factors and develop a nomogram. The discrimination, accuracy, and clinical efficacy of the prediction model were analyzed utilizing the receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve. RESULTS: Through multivariate-logistic-regression analysis, these factors were identified as independent influencing factors for the clinical pregnancy in endometriosis patients undergoing fresh embryo transfer: female age (OR = 0.933, 95% CI = 0.902–0.965, P < 0.001), ASRM stage (OR = 0.384, 95% CI = 0.276–0.532, P < 0.001), postoperative to IVF duration (OR = 0.496, 95% CI = 0.356–0.688, P < 0.001), antral follicle count (AFC) (OR = 1.076, 95% CI = 1.013–1.161, P = 0.045), anti-Müllerian hormone (AMH) (OR = 1.202, 95% CI = 1.073–1.35, P = 0.002), Gonadotrophin-releasing hormone (GnRH) agonist protocol (OR = 1.536, 95% CI = 1.109–2.131, P = 0.01), number of oocytes retrieved (OR = 1.154, 95% CI = 1.067–1.249, P < 0.001), number of high-quality cleavage embryos (OR = 1.261, 95% CI = 1.164–1.369, P < 0.001), and number of embryos transferred (OR = 1.957, 95% CI = 1.435–2.679, P < 0.001). A prediction model for estimating the clinical pregnancy probability in individuals with endometriosis was constructed per these identified independent factors. The ROC showed an area under the curve (AUC) of 0.807 (95% CI = 0.782–0.832) in the model group and 0.800 (95% CI = 0.761–0.84) in the validation group. The Hosmer-Lemeshow test demonstrated no statistically significant difference between predicted and actual clinical pregnancy probabilities (P > 0.05). The clinical decision curve demonstrated that both the model and the validation groups achieved maximum net benefit at threshold probability values of 0.08–0.96 and 0.16–0.96, indicating good clinical efficacy within this range of threshold probabilities. CONCLUSION: Female age, ASRM stage, postoperative to IVF duration, stimulation protocol, AFC, AMH, number of oocytes retrieved, number of high-quality cleavage embryos and number of transferred embryos are independent influencing factors for the clinical pregnancy rate in individuals with endometriosis receiving fresh embryo transfer. The nomogram model based on these factors demonstrates good clinical predictive value and efficacy, providing a basis for clinical prognosis, intervention, and individualized medical treatment planning. BioMed Central 2023-10-31 /pmc/articles/PMC10617063/ /pubmed/37907870 http://dx.doi.org/10.1186/s12884-023-06082-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Zhu, Suqin Liao, Xiuhua Jiang, Wenwen Sun, Yan Chen, Xiaojing Zheng, Beihong Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer |
title | Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer |
title_full | Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer |
title_fullStr | Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer |
title_full_unstemmed | Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer |
title_short | Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer |
title_sort | development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10617063/ https://www.ncbi.nlm.nih.gov/pubmed/37907870 http://dx.doi.org/10.1186/s12884-023-06082-7 |
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