Nomogram Based on Clinical and Laboratory Characteristics of Euploid Embryos Using the Data in PGT-A: a Euploid-prediction Model

Overview

Journal BMC Pregnancy Childbirth

Publisher Biomed Central

Specialty Gynecology & Obstetrics

Date 2022 Mar 18

PMID 35300641

Authors

Xitong Liu

Affiliations

Soon will be listed here.

Abstract

Background: The evaluation of embryo morphology may be inaccurate. A euploid prediction model is needed to provide the best and individualized counseling about embryo selection based on patients and embryo characteristics.

Methods: Our objective was to develop a euploid-prediction model for evaluating blastocyst embryos, based on data from a large cohort of patients undergoing pre-implantation genetic testing for aneuploidy (PGT-A). This retrospective, single-center cohort study included data from 1610 blastocysts which were performed PGT-A with known genetic outcomes. The study population was divided into the training and validation cohorts in a 3:1 ratio. The performance of the euploid-prediction model was quantified using the area under the receiver operating characteristic (ROC) curve (AUC). In addition, a nomogram was drawn to provide quantitative and convenient tools in predicting euploid.

Results: We developed a reliable euploid-prediction model and can directly assess the probability of euploid with the AUC (95%CI) of 0.859 (0.834,0.872) in the training cohort, and 0.852 (0.831,0.879) in the validation cohort, respectively. The euploid-prediction model showed sensitivities of 0.903 and specificities of 0.578.

Conclusions: The euploid-prediction model is a reliable prediction model and can directly assess the probability of euploid.

Citing Articles

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