Non-Invasive Predictive Model may Help in Early Detection of Endometriosis in Infertile Women: Study

A recent study by Jie Zhang and team have successfully crafted a non-invasive predictive model to identify minimal or mild endometriosis in patients who struggle with infertility. The findings were published in the Journal of Minimally Invasive Gynecology.

Infertility affects millions worldwide and identifying the underlying causes is a persistent challenge. By recognizing the significance of early detection in endometriosis-related infertility the team sought to develop a predictive model. This retrospective study was conducted at a tertiary referral center and enrolled a total of 1365 infertility patients who underwent laparoscopy between January 2013 and August 2020.

The study divided patients into a training set (n=910) for model development and a validation set (n=455) for confirmation. This in depth evaluation included sensitivities, specificities, AUCs, the Hosmer-Lemeshow goodness of fit test, NRIs, and IDIs. The final model demonstrated high accuracy by incorporating BMI, dysmenorrhea, dyspareunia, uterosacral tenderness, and serum CA-125. Sensitivities of 87.7% and 93.3%, specificities of 68.6% and 66.4%, and AUCs of 0.84 and 0.85 were recorded for the training and validation sets, respectively.

Uterosacral tenderness emerged as a pivotal predictor and the nomogram underscored good calibration and clinical value. This innovative model promises a cost-effective and less invasive means of identifying minimal or mild endometriosis, a significant factor in infertility.

This study delivers a reliable tool for clinicians as a crucial step towards personalized infertility care. Early identification is a key to prompt intervention which potentially revolutionize the landscape of infertility treatment. This is a significant advancement in empowering healthcare providers with a tool to enhance the diagnosis and treatment of infertility in women.

Source:

Zhang, J., Wang, J., Zhang, J., Liu, J., Xu, Y., Zhu, P., Dai, L., Shu, L., Liu, J., Hou, Z., Diao, F., Liu, J., & Mao, Y. (2023). Developing a predictive model for minimal or mild endometriosis as a clinical screening tool in infertile women: uterosacral tenderness as a key predictor. In Journal of Minimally Invasive Gynecology. Elsevier BV. https://doi.org/10.1016/j.jmig.2023.12.008