Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study

Tan, Xinsha; Xi, Hong-Lin; Yang, Jing; Wang, Wenfeng

doi:10.1155/2021/7822119

Cited by 3 publications

(1 citation statement)

References 29 publications

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“…reported that AFC, AMH, and P levels on the human chorionic gonadotropin (HCG) day were identified as independent predictors of HOR. The nomogram was established with the data of 480 eligible patients ( 26 ). In our study, greater number of cycles were included and a combined prediction model with age, BMI, FSH, AMH, and AFC was developed with good performance.…”

Section: Discussionmentioning

confidence: 99%

A prediction model for high ovarian response in the GnRH antagonist protocol

Jiang,

Cui,

Guo

et al. 2023

Front. Endocrinol.

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BackgroundsThe present study was designed to establish and validate a prediction model for high ovarian response (HOR) in the GnRH antagonist protocol.MethodsIn this retrospective study, the data of 4160 cycles were analyzed following the in vitro fertilization (IVF) at our reproductive medical center from June 2018 to May 2022. The cycles were divided into a training cohort (n=3121) and a validation cohort (n=1039) using a random sampling method. Univariate and multivariate logistic regression analyses were used to screen out the risk factors for HOR, and the nomogram was established based on the regression coefficient of the relevant variables. The area under the receiver operating characteristic curve (AUC), the calibration curve, and the decision curve analysis were used to evaluate the performance of the prediction model.ResultsMultivariate logistic regression analysis revealed that age, body mass index (BMI), follicle-stimulating hormone (FSH), antral follicle count (AFC), and anti-mullerian hormone (AMH) were independent risk factors for HOR (all P< 0.05). The prediction model for HOR was constructed based on these factors. The AUC of the training cohort was 0.884 (95% CI: 0.869–0.899), and the AUC of the validation cohort was 0.884 (95% CI:0.863–0.905).ConclusionThe prediction model can predict the probability of high ovarian response prior to IVF treatment, enabling clinicians to better predict the risk of HOR and guide treatment strategies.

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Section: Discussionmentioning

confidence: 99%

A prediction model for high ovarian response in the GnRH antagonist protocol

Jiang,

Cui,

Guo

et al. 2023

Front. Endocrinol.

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Comparison of anti-Müllerian hormone and antral follicle count in the prediction of ovarian response: a systematic review and meta-analysis

Liu

Pan

et al. 2023

J Ovarian Res

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Background Increasingly studies reported that the Anti-Müllerian hormone (AMH) seems to be a promising and reliable marker of functional ovarian follicle reserve, even better than the AFC test. Our study aimed to conduct a meta-analysis to assess the predictive value of AMH and AFC for predicting poor or high response in IVF treatment. An electronic search was conducted, and the following databases were used: PubMed, EMBASE, and the Cochrane Library (up to 7 May 2022). The bivariate regression model was used to calculate the pooled sensitivity, specificity, and area under the receiver operator characteristic (ROC) curve. Subgroup analyses and meta-regression also were used in the presented study. Overall performance was assessed by estimating pooled ROC curves between AMH and AFC. Results Forty-two studies were eligible for this meta-analysis. Comparison of the summary estimates for the prediction of poor or high response showed significant difference in performance for AMH compared with AFC [poor (sensitivity: 0.80 vs 0.74, P < 0.050; specificity: 0.81 vs 0.85, P < 0.001); high (sensitivity: 0.81 vs 0.87, P < 0.001)]. However, there were no significant differences between the ROC curves of AMH and AFC for predicting high (P = 0.835) or poor response (P = 0.567). The cut-off value was a significant source of heterogeneity in the present study. Conclusions The present meta-analysis demonstrated that both AMH and AFC have a good predictive ability to the prediction of poor or high responses in IVF treatment.

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How high is the risk of thromboembolism in IVF?

Николаева¹,

Smirnova²

2022

Probl. reprod.

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Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study

Cited by 3 publications

References 29 publications

A prediction model for high ovarian response in the GnRH antagonist protocol

A prediction model for high ovarian response in the GnRH antagonist protocol

Comparison of anti-Müllerian hormone and antral follicle count in the prediction of ovarian response: a systematic review and meta-analysis

How high is the risk of thromboembolism in IVF?

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