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Nomogram to predict the probability of clinical pregnancy in women with poor ovarian response undergoing in vitro fertilization/ intracytoplasmic sperm injection cycles

  • Gynecologic Endocrinology and Reproductive Medicine
  • Published:
Archives of Gynecology and Obstetrics Aims and scope Submit manuscript

Abstract

Background

Poor ovarian response (POR) is associated with decreased clinical pregnancy rates, emphasizing the need for develo** clinical prediction models. Such models can improve prognostic accuracy, personalize medical interventions, and ultimately enhance live birth rates among patients with POR.

Objective

This study aims to develop and validate a prognostic model for predicting clinical pregnancy outcomes in individuals with POR undergoing in vitro fertilization/ intracytoplasmic sperm injection (IVF/ICSI) cycles.

Methods

A retrospective cohort of 969 patients with POR undergoing fresh embryo transfer cycles at the Reproductive Center of Fujian Maternal and Child Health Center from January 2018 to January 2022 was included. The cohort was randomly divided into model (n = 678) and validation (n = 291) groups in a 7:3 ratio. A single-factor analysis was performed on the model group to identify variables influencing clinical pregnancy. Optimal variables were selected using LASSO regression, and a clinical prediction model was constructed using multivariate logistic regression analysis. The model's calibration and discrimination were assessed using receiver operating characteristic (ROC) and calibration curves, while the clinical utility was evaluated using decision curve analysis.

Results

Multivariate logistic regression analysis revealed that the age of the women (odds ratio [OR] 0.936, 95% confidence interval [CI] 0.898–0.976, P = 0.002), body mass index (BMI) ≤ 24 (OR 2.748, 95% CI 1.724–4.492, P < 0.001), antral follicle count (AFC) (OR 1.232, 95% CI 1.073–1.416, P = 0.003), anti-Müllerian hormone (AMH) (OR 1.67, 95% CI 1.178–2.376, P = 0.004), number of mature oocytes (OR 1.227, 95% CI 1.075–1.403, P = 0.003), number of embryos transferred (OR 1.692, 95% CI 1.132–2.545, P = 0.011), and transfer of high-quality embryos (OR 3.452, 95% CI 1.548–8.842, P = 0.005) were independent predictors of clinical pregnancy in patients with POR. According to the receiver operating characteristic (ROC) analysis, the prediction model exhibited an area under the curve (AUC) of 0.752 (0.714, 0.789) in the model group and 0.765 (0.708, 0.821) in the validation group. The clinical decision curve demonstrated that the model held maximum clinical utility in both cohorts when the threshold probability of clinical pregnancy ranged from 6–81% to 12–82%, respectively.

Conclusion

Clinical pregnancy outcomes in patients with POR who underwent IVF/ICSI treatment were influenced by several independent factors, including the age of the women, BMI, AFC, AMH, number of mature oocytes, number of embryos transferred, and transfer of high-quality embryos. A clinical prediction model based on these factors exhibited favorable clinical predictive and applicative value. Therefore, this model can serve as a valuable tool for clinical prognosis, intervention, and facilitating personalized medical treatment.

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Data availability

The datasets analyzed during the current study are available from the corresponding author upon reasonable request.

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Funding

This study received support from the Innovation Platform Project of Science and Technology, Fujian Province (2021Y2012), the Key Project on the Integration of Industry, Education and Research Collaborative Innovation of Fujian Province (grant no. 2021YZ034011), the Key Project on the Science and Technology Program of Fujian Health Commission (grant no. 2021ZD01002), the Fujian Provincial Health Technology Project (no. 2022GGA035), the Major Scientific Research Program for Young and Middle-aged Health Professionals of Fujian Province, China (grant no. 2022ZQNZD010), and the Natural Science Foundation of Fujian Province (grant no. 2023J011221).

Author information

Author notes

  1. This work was contributed equally by Suqin Zhu and Wenwen Jiang.

Authors and Affiliations

  1. Center of Reproductive Medicine, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, No. 18 Daoshan Road, Fuzhou City, 350001, Fujian Province, China

    Suqin Zhu, Wenwen Jiang, Yan Sun, Lili Chen, Rongshan Li, **ao**g Chen & Beihong Zheng

  2. Fujian Maternal-Fetal Clinical Medicine Research Center, Fuzhou, 350001, China

    Suqin Zhu

  3. Fujian Key Laboratory of Prenatal Diagnosis and Birth Defect, Fuzhou, 350001, China

    Wenwen Jiang & Beihong Zheng

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  1. Suqin Zhu
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Contributions

CXJ and ZBH conceived and supervised the study. CLL and JWW collected patient data. ZSQ, LRS, and JWW analyzed and interpreted the data. ZSQ, SY, and ZBH contributed to manuscript development. All authors have reviewed and approved the final manuscript.

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Correspondence to **ao**g Chen or Beihong Zheng.

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Zhu, S., Jiang, W., Sun, Y. et al. Nomogram to predict the probability of clinical pregnancy in women with poor ovarian response undergoing in vitro fertilization/ intracytoplasmic sperm injection cycles. Arch Gynecol Obstet (2024). https://doi.org/10.1007/s00404-024-07598-9

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