{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T04:51:56Z","timestamp":1791348716488,"version":"4.3.1"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T00:00:00Z","timestamp":1791331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>\n                      To investigate the association between growth hormone (GH) pretreatment duration and cumulative live birth (CLB), identify key prognostic factors, and develop predictive models using logistic regression (LR) and machine learning (ML) algorithms among women undergoing\n                      <jats:italic>in vitro<\/jats:italic>\n                      fertilization (IVF) with GH supplementation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective cohort study of women undergoing IVF\/intracytoplasmic sperm injection (ICSI) with GH between February 2015 and June 2023 at a single tertiary center. Five models were developed: LR, random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and support vector machine (SVM). Performance was assessed with cross-validation and bootstrap resampling. AUROC and Brier scores evaluated discrimination and calibration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 1,782 women, 763 (42.82%) achieved at least one live birth. Maternal age, anti-M\u00fcllerian hormone (AMH), antral follicle count (AFC), the assisted reproductive technology (ART) cycle number, and GH duration were significant predictors. LR performed best (AUROC 0.782; Brier 0.187), showing strong calibration and interpretability. ML models had moderate discrimination but inferior calibration. AMH, AFC, and GH duration were key predictors across all methods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Both logistic regression and machine learning effectively predicted CLB after GH-pretreated IVF, but LR provided favorable discrimination, calibration, and interpretability. GH pretreatment \u22652 months was independently associated with higher odds of cumulative live birth.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1967517","type":"journal-article","created":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T04:47:04Z","timestamp":1791348424000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting cumulative live birth after IVF with growth hormone supplementation: the role of pretreatment duration and machine learning-based models"],"prefix":"10.3389","volume":"17","author":[{"given":"Yufeng","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Gynaecology, The First People's Hospital of Jiashan, Jiashan Hospital Affiliated to Jiaxing University","place":["Jiaxing, Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyi","family":"Dai","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Wenzhou Hospital of Integrated Chinese and Western Medicine","place":["Wenzhou, Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peiyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Reproductive Medicine Center, The First Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chang","family":"Liu","sequence":"additional","affiliation":[{"name":"Reproductive Medicine Center, The First Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,7]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1097\/gco.0b013e328338493f","article-title":"Cumulative live-birth rates after assisted reproductive technology","volume":"22","author":"Moragianni","year":"2010","journal-title":"Curr Opin Obstet Gynecol"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.3390\/reprodmed2040016","article-title":"A 10-year perspective on the utility of three adjuvants often used in IVF: Growth hormone, melatonin and DHEA","volume":"2","author":"Hinchliffe","year":"2021","journal-title":"Reprod Med"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1080\/09513590.2019.1590545","article-title":"Growth hormone co-treatment on controlled ovarian stimulation in normal ovarian response women can improve embryo quality","volume":"35","author":"Liu","year":"2019","journal-title":"Gynecol Endocrinol"},{"key":"B4","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1186\/s12884-020-03004-9","article-title":"Does growth hormone supplementation improve oocyte competence and IVF outcomes in patients with poor embryonic development? A randomized controlled trial","volume":"20","author":"Li","year":"2020","journal-title":"BMC Pregnancy Childbirth"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1016\/j.fertnstert.2024.03.003","article-title":"Predictors of success after in vitro fertilization","volume":"121","author":"Shingshetty","year":"2024","journal-title":"Fertil Steril"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.3390\/jcm12030955","article-title":"The advantage of growth hormone alone as an adjuvant therapy in advanced age and BMI \u2265 24 kg\/m(2) with in vitro fertilization failure due to poor embryo quality","volume":"12","author":"Jiang","year":"2023","journal-title":"J Clin Med"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1016\/j.fertnstert.2020.09.159","article-title":"Evaluating predictive models in reproductive medicine","volume":"114","author":"Curchoe","year":"2020","journal-title":"Fertil Steril"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1002\/rmb2.12649","article-title":"A machine learning model for predicting fertilization following short-term insemination using embryo images","volume":"24","author":"Saito","year":"2025","journal-title":"Reprod Med Biol"},{"key":"B9","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1186\/s12958-025-01351-w","article-title":"Application of a methodological framework for the development and multicenter validation of reliable artificial intelligence in embryo evaluation","volume":"23","author":"Gilboa","year":"2025","journal-title":"Reprod Biol Endocrinol"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1016\/j.rbmo.2025.104855","article-title":"Artificial intelligence in assisted reproductive technology: separating the dream from reality","volume":"50","author":"Cohen","year":"2025","journal-title":"Reprod BioMed Online"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2025.1556681","article-title":"Comparative analysis of convolutional neural networks and traditional machine learning models for IVF live birth prediction: a retrospective analysis of 48514 IVF cycles and an evaluation of deployment feasibility in resource-constrained settings","volume":"16","author":"Liu","year":"2025","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B12","doi-asserted-by":"publisher","first-page":"3661","DOI":"10.1038\/s41467-025-58744-z","article-title":"Machine learning center-specific models show improved IVF live birth predictions over US national registry-based model","volume":"16","author":"Yao","year":"2025","journal-title":"Nat Commun"},{"key":"B13","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1186\/s12884-025-07433-2","article-title":"Predictive modeling of pregnancy outcomes utilizing multiple machine learning techniques for in vitro fertilization-embryo transfer","volume":"25","author":"Bai","year":"2025","journal-title":"BMC Pregnancy Childbirth"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.3390\/biology14050556","article-title":"Bioinformatic analysis of complex in vitro fertilization data and predictive model design based on machine learning: The age paradox in reproductive health","volume":"14","author":"Lantzi","year":"2025","journal-title":"Biol (Basel)"},{"key":"B15","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1186\/s12877-025-05840-w","article-title":"A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults","volume":"25","author":"Peng","year":"2025","journal-title":"BMC Geriatr"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1177\/0300060517704140","article-title":"Predicting the outcome of different protocols of in vitro fertilization with anti-Mu\u00fcllerian hormone levels in patients with polycystic ovary syndrome","volume":"45","author":"Chen","year":"2017","journal-title":"J Int Med Res"},{"key":"B17","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1016\/j.fertnstert.2017.06.005","article-title":"The international glossary on infertility and fertility care, 2017","volume":"108","author":"Zegers-Hochschild","year":"2017","journal-title":"Fertil Steril"},{"key":"B18","doi-asserted-by":"publisher","first-page":"32083","DOI":"10.1038\/s41598-024-83781-x","article-title":"Machine learning algorithms in constructing prediction models for assisted reproductive technology (ART) related live birth outcomes","volume":"14","author":"Peng","year":"2024","journal-title":"Sci Rep"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"key":"B20","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.ogc.2014.09.005","article-title":"Age-related infertility","volume":"42","author":"Crawford","year":"2015","journal-title":"Obstet Gynecol Clin North Am"},{"key":"B21","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1186\/s12884-025-07613-0","article-title":"Effect of repeated controlled ovarian stimulation on pregnancy outcomes in fresh embryo transfer cycles: a retrospective cohort study","volume":"25","author":"Wang","year":"2025","journal-title":"BMC Pregnancy Childbirth"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1093\/humupd\/dmae032","article-title":"Development and validation of a gonadotropin dose selection model for optimized ovarian stimulation in IVF\/ICSI: an individual participant data meta-analysis","volume":"31","author":"Schouten","year":"2025","journal-title":"Hum Reprod Update"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2019.00094","article-title":"Advanced maternal age in IVF: Still a challenge? The present and the future of its treatment","volume":"10","author":"Ubaldi","year":"2019","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.5935\/1518-0557.20190043","article-title":"Can we predict the IVF\/ICSI live birth rate","volume":"23","author":"Metello","year":"2019","journal-title":"JBRA Assist Reprod"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.81568","article-title":"Artificial intelligence in assisted reproductive technology: A new era in fertility treatment","volume":"17","author":"Orovou","year":"2025","journal-title":"Cureus"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2025.1595970","article-title":"Comprehensive mathematical modeling of age-dependent oocyte quality and quantity for predicting live birth rate","volume":"16","author":"Sujino","year":"2025","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1210\/er.21.2.200","article-title":"Initial and cyclic recruitment of ovarian follicles","volume":"21","author":"McGee","year":"2000","journal-title":"Endocr Rev"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.3390\/ijms252212197","article-title":"Abnormalities of oocyte maturation: Mechanisms and implications","volume":"25","author":"Baldini","year":"2024","journal-title":"Int J Mol Sci"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1007\/s43032-022-01147-y","article-title":"Growth hormone promotes oocyte maturation in vitro by protecting mitochondrial function and reducing apoptosis","volume":"30","author":"Deng","year":"2023","journal-title":"Reprod Sci"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.1016\/j.ando.2021.05.003","article-title":"Growth hormone replacement improved oocyte quality in a patient with hypopituitarism: A study of follicular fluid","volume":"82","author":"Scheffler","year":"2021","journal-title":"Ann Endocrinol (Paris)"},{"key":"B31","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1186\/s12958-025-01374-3","article-title":"Exploring the potential benefits of growth hormone co-treatment on embryo quality in IVF: a randomized controlled open-label trial","volume":"23","author":"Tang","year":"2025","journal-title":"Reprod Biol Endocrinol"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2020.00001","article-title":"Growth hormone supplementation may not improve live birth rate in poor responders","volume":"11","author":"Zhu","year":"2020","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.26574\/maedica.2022.17.2.336","article-title":"Effects of adjuvant growth hormone therapy on poor ovarian responders in assisted reproductive technology","volume":"17","author":"Zafardoust","year":"2022","journal-title":"Maedica (Bucur)"},{"key":"B34","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.fertnstert.2020.03.007","article-title":"Growth hormone cotreatment for poor responders undergoing in vitro fertilization cycles: a systematic review and meta-analysis","volume":"114","author":"Cozzolino","year":"2020","journal-title":"Fertil Steril"},{"key":"B35","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1093\/humrep\/deae251","article-title":"Empirical use of growth hormone in IVF is useless: the largest randomized controlled trial","volume":"40","author":"Mourad","year":"2025","journal-title":"Hum Reprod"},{"key":"B36","doi-asserted-by":"publisher","DOI":"10.1186\/s12884-026-09825-4","article-title":"Prolonged growth hormone pretreatment is associated with improved embryo quality in women with poor quality embryos in previous IVF cycles","author":"Liu","year":"2026","journal-title":"BMC Pregnancy Childbirth"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2023.1215755","article-title":"Clinical evidence of growth hormone for infertile women with diminished ovarian reserve undergoing IVF: a systematic review and meta-analysis","volume":"14","author":"Lin","year":"2023","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.1016\/j.fertnstert.2018.09.003","article-title":"Why is growth hormone underutilized for our most difficult IVF couples","volume":"110","author":"Meldrum","year":"2018","journal-title":"Fertil Steril"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1097\/md.0000000000006443","article-title":"The influence of different growth hormone addition protocols to poor ovarian responders on clinical outcomes in controlled ovary stimulation cycles: A systematic review and meta-analysis","volume":"96","author":"Li","year":"2017","journal-title":"Med (Baltimore)"}],"container-title":["Frontiers in Endocrinology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fendo.2026.1967517\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T04:47:15Z","timestamp":1791348435000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fendo.2026.1967517\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,7]]},"references-count":39,"alternative-id":["10.3389\/fendo.2026.1967517"],"URL":"https:\/\/doi.org\/10.3389\/fendo.2026.1967517","relation":{},"ISSN":["1664-2392"],"issn-type":[{"value":"1664-2392","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,7]]},"article-number":"1967517"}}