Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study

Objective. To develop and validate a prediction model for high ovarian response in in vitro fertilization-embryo transfer (IVF-ET) cycles. Methods. Totally, 480 eligible outpatients with infertility who underwent IVF-ET were selected and randomly divided into the training set for developing the pred...

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Veröffentlicht in:Computational and mathematical methods in medicine 2021-10, Vol.2021, p.7822119-12
Hauptverfasser: Tan, Xinsha, Xi, Honglin, Yang, Jing, Wang, Wenfeng
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container_title Computational and mathematical methods in medicine
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creator Tan, Xinsha
Xi, Honglin
Yang, Jing
Wang, Wenfeng
description Objective. To develop and validate a prediction model for high ovarian response in in vitro fertilization-embryo transfer (IVF-ET) cycles. Methods. Totally, 480 eligible outpatients with infertility who underwent IVF-ET were selected and randomly divided into the training set for developing the prediction model and the testing set for validating the model. Univariate and multivariate logistic regressions were carried out to explore the predictive factors of high ovarian response, and then, the prediction model was constructed. Nomogram was plotted for visualizing the model. Area under the receiver-operating characteristic (ROC) curve, Hosmer-Lemeshow test and calibration curve were used to evaluate the performance of the prediction model. Results. Antral follicle count (AFC), anti-Müllerian hormone (AMH) at menstrual cycle day 3 (MC3), and progesterone (P) level on human chorionic gonadotropin (HCG) day were identified as the independent predictors of high ovarian response. The value of area under the curve (AUC) for our multivariate model reached 0.958 (95% CI: 0.936-0.981) with the sensitivity of 0.916 (95% CI: 0.863-0.953) and the specificity of 0.911 (95% CI: 0.858-0.949), suggesting the good discrimination of the prediction model. The Hosmer-Lemeshow test and the calibration curve both suggested model’s good calibration. Conclusion. The developed prediction model had good discrimination and accuracy via internal validation, which could help clinicians efficiently identify patients with high ovarian response, thereby improving the pregnancy rates and clinical outcomes in IVF-ET cycles. However, the conclusion needs to be confirmed by more related studies.
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To develop and validate a prediction model for high ovarian response in in vitro fertilization-embryo transfer (IVF-ET) cycles. Methods. Totally, 480 eligible outpatients with infertility who underwent IVF-ET were selected and randomly divided into the training set for developing the prediction model and the testing set for validating the model. Univariate and multivariate logistic regressions were carried out to explore the predictive factors of high ovarian response, and then, the prediction model was constructed. Nomogram was plotted for visualizing the model. Area under the receiver-operating characteristic (ROC) curve, Hosmer-Lemeshow test and calibration curve were used to evaluate the performance of the prediction model. Results. Antral follicle count (AFC), anti-Müllerian hormone (AMH) at menstrual cycle day 3 (MC3), and progesterone (P) level on human chorionic gonadotropin (HCG) day were identified as the independent predictors of high ovarian response. The value of area under the curve (AUC) for our multivariate model reached 0.958 (95% CI: 0.936-0.981) with the sensitivity of 0.916 (95% CI: 0.863-0.953) and the specificity of 0.911 (95% CI: 0.858-0.949), suggesting the good discrimination of the prediction model. The Hosmer-Lemeshow test and the calibration curve both suggested model’s good calibration. Conclusion. The developed prediction model had good discrimination and accuracy via internal validation, which could help clinicians efficiently identify patients with high ovarian response, thereby improving the pregnancy rates and clinical outcomes in IVF-ET cycles. However, the conclusion needs to be confirmed by more related studies.</description><identifier>ISSN: 1748-670X</identifier><identifier>EISSN: 1748-6718</identifier><identifier>DOI: 10.1155/2021/7822119</identifier><identifier>PMID: 34697556</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Adult ; Computational Biology ; Embryo Transfer - adverse effects ; Female ; Fertilization in Vitro - adverse effects ; Humans ; Longitudinal Studies ; Models, Biological ; Multivariate Analysis ; Nomograms ; Ovarian Hyperstimulation Syndrome - etiology ; Ovulation Induction - adverse effects ; Ovulation Induction - methods ; Ovulation Induction - statistics &amp; numerical data ; Pregnancy ; Pregnancy Rate ; Risk Factors ; ROC Curve</subject><ispartof>Computational and mathematical methods in medicine, 2021-10, Vol.2021, p.7822119-12</ispartof><rights>Copyright © 2021 Xinsha Tan et al.</rights><rights>Copyright © 2021 Xinsha Tan et al. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c420t-c686ce551b997d12aac252a1a40085b207e5334be6ea05853f12de5fe50b66e43</citedby><cites>FETCH-LOGICAL-c420t-c686ce551b997d12aac252a1a40085b207e5334be6ea05853f12de5fe50b66e43</cites><orcidid>0000-0002-0248-5625 ; 0000-0002-3286-0772 ; 0000-0003-0354-0056</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541868/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541868/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34697556$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Anom Ahmad, Siti</contributor><creatorcontrib>Tan, Xinsha</creatorcontrib><creatorcontrib>Xi, Honglin</creatorcontrib><creatorcontrib>Yang, Jing</creatorcontrib><creatorcontrib>Wang, Wenfeng</creatorcontrib><title>Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study</title><title>Computational and mathematical methods in medicine</title><addtitle>Comput Math Methods Med</addtitle><description>Objective. To develop and validate a prediction model for high ovarian response in in vitro fertilization-embryo transfer (IVF-ET) cycles. Methods. Totally, 480 eligible outpatients with infertility who underwent IVF-ET were selected and randomly divided into the training set for developing the prediction model and the testing set for validating the model. Univariate and multivariate logistic regressions were carried out to explore the predictive factors of high ovarian response, and then, the prediction model was constructed. Nomogram was plotted for visualizing the model. Area under the receiver-operating characteristic (ROC) curve, Hosmer-Lemeshow test and calibration curve were used to evaluate the performance of the prediction model. Results. Antral follicle count (AFC), anti-Müllerian hormone (AMH) at menstrual cycle day 3 (MC3), and progesterone (P) level on human chorionic gonadotropin (HCG) day were identified as the independent predictors of high ovarian response. The value of area under the curve (AUC) for our multivariate model reached 0.958 (95% CI: 0.936-0.981) with the sensitivity of 0.916 (95% CI: 0.863-0.953) and the specificity of 0.911 (95% CI: 0.858-0.949), suggesting the good discrimination of the prediction model. The Hosmer-Lemeshow test and the calibration curve both suggested model’s good calibration. Conclusion. The developed prediction model had good discrimination and accuracy via internal validation, which could help clinicians efficiently identify patients with high ovarian response, thereby improving the pregnancy rates and clinical outcomes in IVF-ET cycles. However, the conclusion needs to be confirmed by more related studies.</description><subject>Adult</subject><subject>Computational Biology</subject><subject>Embryo Transfer - adverse effects</subject><subject>Female</subject><subject>Fertilization in Vitro - adverse effects</subject><subject>Humans</subject><subject>Longitudinal Studies</subject><subject>Models, Biological</subject><subject>Multivariate Analysis</subject><subject>Nomograms</subject><subject>Ovarian Hyperstimulation Syndrome - etiology</subject><subject>Ovulation Induction - adverse effects</subject><subject>Ovulation Induction - methods</subject><subject>Ovulation Induction - statistics &amp; numerical data</subject><subject>Pregnancy</subject><subject>Pregnancy Rate</subject><subject>Risk Factors</subject><subject>ROC Curve</subject><issn>1748-670X</issn><issn>1748-6718</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><recordid>eNp9kc1uEzEURi0EoqWwY428RIKhtmfscVhUqkr_pFRFUCp21p3xncTIYwd7EhSegMfutEkj2LC635WPjm19hLzm7APnUh4KJvhhrYXgfPKE7PO60oWquX66y-z7HnmR8w_GJK8lf072ykpNainVPvnzCVfo46LHMFAIlt6CdxYGFwONHf2c0Lr2YbuKFj3tYqIXbjan1ytIDgL9gnkRQ0bqAr0M9NYNKdIzTIPz7veDpzjtm7SO9CZByB2mj_SYTmOYuWFpXQBPv45h_ZI868BnfLWdB-Tb2enNyUUxvT6_PDmeFm0l2FC0SqsWpeTNZFJbLgBaIQVwqBjTshGsRlmWVYMKgUkty44Li7JDyRqlsCoPyNHGu1g2Pdp2_HcCbxbJ9ZDWJoIz_54ENzezuDJaVlwrPQrebgUp_lxiHkzvcoveQ8C4zEZIrSrJlBIj-n6DtinmnLDbXcOZuS_P3JdntuWN-Ju_n7aDH9sagXcbYO6ChV_u_7o7bNikIg</recordid><startdate>20211016</startdate><enddate>20211016</enddate><creator>Tan, Xinsha</creator><creator>Xi, Honglin</creator><creator>Yang, Jing</creator><creator>Wang, Wenfeng</creator><general>Hindawi</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-0248-5625</orcidid><orcidid>https://orcid.org/0000-0002-3286-0772</orcidid><orcidid>https://orcid.org/0000-0003-0354-0056</orcidid></search><sort><creationdate>20211016</creationdate><title>Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study</title><author>Tan, Xinsha ; Xi, Honglin ; Yang, Jing ; Wang, Wenfeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c420t-c686ce551b997d12aac252a1a40085b207e5334be6ea05853f12de5fe50b66e43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adult</topic><topic>Computational Biology</topic><topic>Embryo Transfer - adverse effects</topic><topic>Female</topic><topic>Fertilization in Vitro - adverse effects</topic><topic>Humans</topic><topic>Longitudinal Studies</topic><topic>Models, Biological</topic><topic>Multivariate Analysis</topic><topic>Nomograms</topic><topic>Ovarian Hyperstimulation Syndrome - etiology</topic><topic>Ovulation Induction - adverse effects</topic><topic>Ovulation Induction - methods</topic><topic>Ovulation Induction - statistics &amp; numerical data</topic><topic>Pregnancy</topic><topic>Pregnancy Rate</topic><topic>Risk Factors</topic><topic>ROC Curve</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tan, Xinsha</creatorcontrib><creatorcontrib>Xi, Honglin</creatorcontrib><creatorcontrib>Yang, Jing</creatorcontrib><creatorcontrib>Wang, Wenfeng</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Computational and mathematical methods in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tan, Xinsha</au><au>Xi, Honglin</au><au>Yang, Jing</au><au>Wang, Wenfeng</au><au>Anom Ahmad, Siti</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study</atitle><jtitle>Computational and mathematical methods in medicine</jtitle><addtitle>Comput Math Methods Med</addtitle><date>2021-10-16</date><risdate>2021</risdate><volume>2021</volume><spage>7822119</spage><epage>12</epage><pages>7822119-12</pages><issn>1748-670X</issn><eissn>1748-6718</eissn><abstract>Objective. To develop and validate a prediction model for high ovarian response in in vitro fertilization-embryo transfer (IVF-ET) cycles. Methods. Totally, 480 eligible outpatients with infertility who underwent IVF-ET were selected and randomly divided into the training set for developing the prediction model and the testing set for validating the model. Univariate and multivariate logistic regressions were carried out to explore the predictive factors of high ovarian response, and then, the prediction model was constructed. Nomogram was plotted for visualizing the model. Area under the receiver-operating characteristic (ROC) curve, Hosmer-Lemeshow test and calibration curve were used to evaluate the performance of the prediction model. Results. Antral follicle count (AFC), anti-Müllerian hormone (AMH) at menstrual cycle day 3 (MC3), and progesterone (P) level on human chorionic gonadotropin (HCG) day were identified as the independent predictors of high ovarian response. The value of area under the curve (AUC) for our multivariate model reached 0.958 (95% CI: 0.936-0.981) with the sensitivity of 0.916 (95% CI: 0.863-0.953) and the specificity of 0.911 (95% CI: 0.858-0.949), suggesting the good discrimination of the prediction model. The Hosmer-Lemeshow test and the calibration curve both suggested model’s good calibration. Conclusion. The developed prediction model had good discrimination and accuracy via internal validation, which could help clinicians efficiently identify patients with high ovarian response, thereby improving the pregnancy rates and clinical outcomes in IVF-ET cycles. 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subjects Adult
Computational Biology
Embryo Transfer - adverse effects
Female
Fertilization in Vitro - adverse effects
Humans
Longitudinal Studies
Models, Biological
Multivariate Analysis
Nomograms
Ovarian Hyperstimulation Syndrome - etiology
Ovulation Induction - adverse effects
Ovulation Induction - methods
Ovulation Induction - statistics & numerical data
Pregnancy
Pregnancy Rate
Risk Factors
ROC Curve
title Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study
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