{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T16:54:34Z","timestamp":1790009674615,"version":"4.0.1"},"reference-count":110,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T00:00:00Z","timestamp":1778112000000},"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:p>Ovarian response to controlled ovarian stimulation (COS) is a core determinant of assisted reproductive technology (ART) success, with marked interindividual variability. Accurate and individualized prediction is essential to optimize treatment safety and efficacy. Traditional static predictors include age, BMI, AMH, AFC, FSH\/LH ratio, and inhibin B. Recently, dynamic indices such as FORT, FOI, OSI, and ORPI have improved real time evaluation of ovarian responsiveness. Genetic polymorphisms, epigenetic regulation, and environmental exposures further modulate ovarian sensitivity to gonadotropins. This review proposes a novel Integrated Multi-dimensional Ovarian Response Prediction (IMORP) framework that combines static reserve, dynamic responsiveness, genetics, and environment to guide personalized COS. We grade evidence levels, critically appraise strengths and limitations of each marker, and provide a head to head comparison of dynamic indices. Future directions should integrate multi omics data and clinical parameters to develop molecularly driven predictive models, advancing ART from empirical practice to precision medicine.<\/jats:p>","DOI":"10.3389\/fendo.2026.1793202","type":"journal-article","created":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T04:49:17Z","timestamp":1778129357000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Assessment indicators of ovarian response during controlled ovarian stimulation: influencing factors and clinical value"],"prefix":"10.3389","volume":"17","author":[{"given":"Huishu","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Reproductive Medicine, Binzhou Medical University Hospital, Binzhou Medical University","place":["Binzhou, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Feng","sequence":"additional","affiliation":[{"name":"Department 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