A nomogram for distinguishing ovarian endometrioma in patients with endometriosis: a retrospective study based on clinical indicators

Background Among the subtypes of endometriosis (EMs), ovarian endometrioma (OE) causes the most direct and progressive damage to ovarian reserve function. This study aimed to identify independent risk factors for OE in patients with EMs, and to develop and validate a clinical classification model to support identification of patients with coexisting OE.

A retrospective study was conducted on 342 patients with pathologically confirmed EMs admitted to the First Affiliated Hospital of Guangxi University of Chinese Medicine from January 2021 to December 2025. Among them, 103 patients had OE (OE group) and 239 had other types of EMs (non-OE group). Patients were randomly divided into training and validation sets at a 7:3 ratio. Least absolute shrinkage and selection operator (LASSO) regression was used for preliminary feature selection, followed by univariate and multivariate logistic regression analyses to identify independent correlates of OE. A nomogram classification model was subsequently constructed. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC), calibration was evaluated using calibration curves comparing predicted probabilities with observed outcomes, and clinical utility was assessed using decision curve analysis (DCA).

Multivariate logistic regression analysis revealed that history of dysmenorrhea (OR = 60.44, 95%CI: 20.95–213.90), infertility (OR = 13.10, 95%CI: 4.85–40.21), elevated fibrinogen levels (OR = 1.84, 95%CI: 1.13–3.01), and decreased lymphocyte count (OR = 0.42, 95%CI: 0.16–0.99) were independent correlates of OE in patients with EMs (all P < 0.05). The nomogram model constructed based on these factors demonstrated excellent discrimination in both the training and validation sets (AUC = 0.945 and 0.948, respectively), good calibration, and positive clinical net benefit across a wide range of threshold probabilities as shown by DCA.

This study successfully developed and internally validated a nomogram based on history of dysmenorrhea, infertility, fibrinogen level, and lymphocyte count for estimating the probability of coexisting OE in patients with pathologically confirmed EMs. By integrating simple clinical symptoms with routine laboratory parameters, this model provides a practical tool for identifying patients with OE among those with EMs, potentially facilitating more targeted imaging and clinical management. However, because of the cross-sectional design, the model does not predict future incident OE; prospective validation is needed. Funding This work was supported by the National Famous Traditional Chinese Medicine Experts Inheritance Studio Construction Project in the Field of Maternal and Child Health, the National Natural Science Foundation of China (grant numbers 82460948 and 81960884), the Innovation Project of Guangxi Graduate Education of GXUCM (grant number YCBXJ2025030), and the Guangxi Natural Science Foundation (grant number 2023GXNSFAA026223). Author information Authors and Affiliations Corresponding author Ethics declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of the First Affiliated Hospital of Guangxi University of Chinese Medicine (Approval No: YJS2023-048). The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The requirement for informed consent was waived by the Ethics Committee of the First Affiliated Hospital of Guangxi University of Chinese Medicine due to the retrospective nature of the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Lin Zhong made equal contribution to this article as the first author and is the co-first author. Supplementary Information Rights and permissions Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. About this article Cite this article Shan, L., Zhong, L., Guochu, H. et al. A nomogram for distinguishing ovarian endometrioma in patients with endometriosis: a retrospective study based on clinical indicators. BMC Women's Health (2026). https://doi.org/10.1186/s12905-026-04785-5 Received: Accepted: Published: DOI: https://doi.org/10.1186/s12905-026-04785-5