Differential diagnosis of ovarian endometriosis cyst versus ovarian cystadenoma based on serum lactate dehydrogenase combined with CA-125 and CA19-9: A retrospective cohort study

This study aims to construct and validate a nomogram for the differential diagnosis of ovarian endometriosis cyst versus ovarian cystadenoma. We retrospectively studied the clinical characteristics of patients with ovarian endometriosis cysts and ovarian cystadenomas from January 1, 2021, to June 1, 2022. Independent risk factors for differential diagnosis were investigated using univariate and multivariate logistic regression analyses. Based on these factors, a differential diagnosis of ovarian endometriosis cyst versus ovarian cystadenoma was established. The performance of the nomogram model was assessed by internal validation using bootstrapping resampling. Decision curve analysis (DCA) was performed to evaluate the net clinical benefit of the model. Immunohistochemistry showed that lactate dehydrogenase (LDH) A was overexpressed in ectopic endometrial tissues compared to that in normal endometrial tissues. In multivariate analysis, LDH, CA-125, and CA19-9 were identified as independent risk factors for the differential diagnosis of ovarian endometriosis cyst versus ovarian cystadenoma. LDH levels >135.50 U/L combined with CA-125 levels >25.20 U/mL and CA19-9 levels >13.59 U/mL as single covariates had a high value in the differential diagnosis of ovarian endometriosis cysts versus ovarian cystadenoma. The area under the receiver operating characteristic curve (ROC) of the nomogram constructed using LDH, CA-125, and CA19-9 expression data was 0.873 (95% CI, 0.827-0.920), and the bootstrap-validated concordance index (C-index) was 0.871. Decision curve analysis confirmed that the nomogram model had excellent clinical utility. Based on serum lactate dehydrogenase combined with CA-125 and CA19-9, we constructed and validated a nomogram for the differential diagnosis of ovarian endometriosis cyst versus ovarian cystadenoma to help physicians formulate the optimal treatment strategy.