Xiaolin Zhong,1,* Weihong Lu,1,* Qi Zhang,1 Jie Dong,1 Hongyang Xiao,2 Ruiqin Tu2 

1Department of Gynecology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 366100, People’s Republic of China; 2Department of Gynecology, Zhongshan Hospital, Fudan University, Shanghai, 200035, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Hongyang Xiao; Ruiqin Tu, Department of Gynecology, Zhongshan Hospital, Fudan University, No. 180, Fenglin Road, Xuhui District, Shanghai, 200035, People’s Republic of China, Tel +86-592-3568682, Email xhy2024521@163.com; xiao.hongyang@zs-hospital.sh.cn; tu.ruiqin@zs-hospital.sh.cn

Objective: This study aims to investigate the association between the dynamics of routine metabolic markers and endometriosis severity.
Methods: A retrospective analysis was conducted on patients diagnosed with endometriosis at Zhongshan Hospital, Xiamen, affiliated with Fudan University. The collected data encompassed demographic details and biochemical indicators related to lipid, hepatobiliary, renal metabolism, and electrolyte balance. Independent influencing factors were screened by univariate logistic regression and statistically significant variables were included in the model for adjustment. Restricted cubic spline (RCS) models were also plotted to analyze the nonlinear relationship between factors and endometriosis severity. The receiver operating characteristic (ROC) curve was used to validate the discriminative ability of independent influencing factors.
Results: Ninety-four patients were enrolled in the study, including 32 at stage IV as classified by the American Society for Reproductive Medicine (ASRM) staging. Univariate analysis identified fasting blood glucose (FBG), total protein, direct bilirubin, total bilirubin (TBil) and glutamic-pyruvic transaminase (ALT) as significant metabolic indicators. Additionally, carbohydrate antigen 125 (CA125) and human epididymal protein 4 (HE4) emerged as significant covariates. The RCS analysis revealed a nonlinear association between most metabolic indicators and outcome measures. ROC curve analysis showed that the area under the curve (AUC) of the alanine transaminase (ALT) was above 0.6.
Conclusion: ALT had a negative correlation with the severity of endometriosis and was an independent influencing factor with statistical significance. This finding could offer clinicians non-invasive biomarkers for early detection and precise monitoring of disease progression.

Keywords: endometriosis, metabolic, American Society for Reproductive Medicine staging