{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T04:47:09Z","timestamp":1777870029084,"version":"3.51.4"},"reference-count":29,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T00:00:00Z","timestamp":1764115200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T00:00:00Z","timestamp":1764115200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100011493","name":"Taizhou Municipal Science and Technology Bureau","doi-asserted-by":"publisher","award":["1901ky23"],"award-info":[{"award-number":["1901ky23"]}],"id":[{"id":"10.13039\/501100011493","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["obgyn.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Intl J Gynecology &amp; Obste"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Fetal growth restriction (FGR) is a progressive condition that amplifies risks with advancing gestation. This study develops a time\u2010dependent random survival forest (RSF) model integrating prenatal screening markers to predict FGR and explore temporal factors, aiding clinical decision making for targeted intervention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This was a retrospective cohort study in tertiary hospitals in Taizhou City, China (2016\u20132022) including 27\u2009543 singleton pregnancies with serial prenatal records, excluding major fetal anomalies or incomplete follow\u2010up. An RSF model was developed using gestational week as the time variable and Delphi\u2010defined FGR as the event. The model incorporates maternal biological data, serologic markers, and ultrasound measurements as feature variables. Performance was assessed using time\u2010dependent receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Feature\u2010based cumulative risk curves were employed for interpreting the model. Main outcomes were measured using model validation (C\u2010index, area under the curve [AUC]) and utility (individual prediction curves, feature risk curve).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The RSF model demonstrated high performance (C\u2010index: 0.864), with peak predictive power between 28 and 36\u2009weeks' gestation (AUC: 0.87\u20130.91). It identified both early\u2010 and late\u2010onset FGR. Key predictors included ultrasound markers such as abdominal circumference and femur length. Late\u2010onset FGR was mainly caused by a cumulative mild effect of multiple factors, while early\u2010onset FGR was driven by maternal factors and fetal markers like AFP and E3.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The RSF model outperforms traditional models in accuracy and flexibility, providing dynamic FGR risk predictions and supporting timely clinical intervention.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ijgo.70611","type":"journal-article","created":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T15:10:38Z","timestamp":1764169838000},"page":"940-948","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Development of a time\u2010dependent random survival forest model for predicting\n                    <scp>FGR<\/scp>\n                    based on prenatal screening date"],"prefix":"10.1002","volume":"173","author":[{"given":"Yan","family":"Ruan","sequence":"first","affiliation":[{"name":"Center for Reproductive Medicine, Taizhou Hospital of Zhejiang Province Wenzhou Medical College  Linhai City China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pan\u2010Xi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics &amp; 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