Development and validation of a nomogram model for predicting clinical pregnancy in endometriosis patients undergoing fresh embryo transfer

• Main Authors: Suqin Zhu (Author), Xiuhua Liao (Author), Wenwen Jiang (Author), Yan Sun (Author), Xiaojing Chen (Author), Beihong Zheng (Author)
• Format: Book
• Published: BMC, 2023-10-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12884-023-06082-7; 1471-2393
• Keywords: Endometriosis; Predictive model; Clinical pregnancy; Nomogram; In vitro fertilization; Gynecology and obstetrics; RG1-991
• Source: BMC Pregnancy and Childbirth, Vol 23, Iss 1, Pp 1-11 (2023)

Abstract Purpose To construct and validate a nomogram model for predicting clinical pregnancy in individuals with endometriosis undergoing fersh embryo transfer (ET). Methods A retrospective analysis was conducted on 1630 individuals with endometriosis who underwent in vitro fertilization (IVF) with fresh embryo transfer at the Reproductive Medicine Center of Fujian Maternity and Child Health Hospital from January 2018 to January 2022. The research population was sorted into two groups through random sampling, namely, the model group (n = 1141) and the validation group (n = 489), with a ratio of 7:3. Univariate analysis was utilized to determine the influencing factors for clinical pregnancy in the model group. The LASSO algorithm was utilized to select the optimal matching factors, which were then included in a multifactorial forward stepwise logistic regression to determine independent influencing factors and develop a nomogram. The discrimination, accuracy, and clinical efficacy of the prediction model were analyzed utilizing the receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve. Results Through multivariate-logistic-regression analysis, these factors were identified as independent influencing factors for the clinical pregnancy in endometriosis patients undergoing fresh embryo transfer: female age (OR = 0.933, 95% CI = 0.902-0.965, P < 0.001), ASRM stage (OR = 0.384, 95% CI = 0.276-0.532, P < 0.001), postoperative to IVF duration (OR = 0.496, 95% CI = 0.356-0.688, P < 0.001), antral follicle count (AFC) (OR = 1.076, 95% CI = 1.013-1.161, P = 0.045), anti-Müllerian hormone (AMH) (OR = 1.202, 95% CI = 1.073-1.35, P = 0.002), Gonadotrophin-releasing hormone (GnRH) agonist protocol (OR = 1.536, 95% CI = 1.109-2.131, P = 0.01), number of oocytes retrieved (OR = 1.154, 95% CI = 1.067-1.249, P < 0.001), number of high-quality cleavage embryos (OR = 1.261, 95% CI = 1.164-1.369, P < 0.001), and number of embryos transferred (OR = 1.957, 95% CI = 1.435-2.679, P < 0.001). A prediction model for estimating the clinical pregnancy probability in individuals with endometriosis was constructed per these identified independent factors. The ROC showed an area under the curve (AUC) of 0.807 (95% CI = 0.782-0.832) in the model group and 0.800 (95% CI = 0.761-0.84) in the validation group. The Hosmer-Lemeshow test demonstrated no statistically significant difference between predicted and actual clinical pregnancy probabilities (P > 0.05). The clinical decision curve demonstrated that both the model and the validation groups achieved maximum net benefit at threshold probability values of 0.08-0.96 and 0.16-0.96, indicating good clinical efficacy within this range of threshold probabilities. Conclusion Female age, ASRM stage, postoperative to IVF duration, stimulation protocol, AFC, AMH, number of oocytes retrieved, number of high-quality cleavage embryos and number of transferred embryos are independent influencing factors for the clinical pregnancy rate in individuals with endometriosis receiving fresh embryo transfer. The nomogram model based on these factors demonstrates good clinical predictive value and efficacy, providing a basis for clinical prognosis, intervention, and individualized medical treatment planning.