AUTHOR=Jiang Xiaohua , Liu Ruijun , Liao Ting , He Ye , Li Caihua , Guo Peipei , Zhou Ping , Cao Yunxia , Wei Zhaolian 

TITLE=A Predictive Model of Live Birth Based on Obesity and Metabolic Parameters in Patients With PCOS Undergoing Frozen-Thawed Embryo Transfer

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 12 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2021.799871

DOI=10.3389/fendo.2021.799871

ISSN=1664-2392

ABSTRACT=Abstract:
Aims: To determine the clinical predictors of live birth in women with polycystic ovary syndrome (PCOS) undergoing frozen-thawed embryo transfer (F-ET), and to determine whether these parameters can be used to develop a clinical nomogram model capable of predicting live birth outcomes for these women.
Methods: In total, 1158 PCOS patients that were clinically pregnant following F-ET treatment were retrospectively enrolled in this study, and randomly divided into the training cohort (n = 928) and the validation cohort (n = 230) in an 8:2 ratio. Relevant risk factors were selected via a logistic regression analysis approach based on the data of patients in the training cohort, and odds ratios (ORs) were calculated. Nomogram was constructed based on the relevant risk factors, and its performance was assessed based on its calibration and its discriminative ability. 
Results: In total, 20 variables were analyzed in the present study, of which five were found to be independently associated with the odds of live birth through univariate and multivariate logistic regression analyses, including advanced age, obesity, total cholesterol (TC), triglycerides (TG), and insulin resistance (IR). Having advanced age (OR:0.499, 95% confidence interval [CI]: 0.257 – 967), being obese (OR:0.506, 95% CI: 0.306 - 0.837), having higher TC levels (OR: 0.528, 95% CI: 0.423 - 0.660), having higher TG levels (OR: 0.585, 95% CI: 0.465 - 737), and exhibiting IR (OR:0.611, 95% CI: 0.416 - 0.896) were all independently associated with a reduced chance of achieving a live birth. The predictive nomogram incorporating these five variables was found to exhibit good calibration and discriminatory capabilities, with an area under the curve (AUC) for the training group of 0.750 (95% CI, 0.709 - 0.788). In the independent validation cohort of patients, the model also exhibited satisfactory goodness-of-fit and discriminative capabilities, with an AUC of 0.708 (95% CI, 0.615 - 0.781).
Conclusions: The nomogram developed in this study may be of value as a tool for predicting the odds of live birth for PCOS patients undergoing F-ET, and has the potential to make pre-transfer management more efficient.