Zhong Xiaolin, Lu Weihong, Zhang Qi, Dong Jie, Xiao Hongyang, Tu Ruiqin
Department of Gynecology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 366100, People's Republic of China.
Department of Gynecology, Zhongshan Hospital, Fudan University, Shanghai, 200035, People's Republic of China.
Int J Gen Med. 2025 Sep 4;18:5183-5193. doi: 10.2147/IJGM.S537848. eCollection 2025.
This study aims to investigate the association between the dynamics of routine metabolic markers and endometriosis severity.
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.
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.
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.
本研究旨在探讨常规代谢标志物动态变化与子宫内膜异位症严重程度之间的关联。
对复旦大学附属厦门中山医院诊断为子宫内膜异位症的患者进行回顾性分析。收集的数据包括人口统计学细节以及与脂质、肝胆、肾脏代谢和电解质平衡相关的生化指标。通过单因素逻辑回归筛选独立影响因素，并将具有统计学意义的变量纳入模型进行调整。还绘制了受限立方样条（RCS）模型以分析因素与子宫内膜异位症严重程度之间的非线性关系。采用受试者工作特征（ROC）曲线来验证独立影响因素的判别能力。
94例患者纳入本研究，其中根据美国生殖医学学会（ASRM）分期为IV期的有32例。单因素分析确定空腹血糖（FBG）、总蛋白、直接胆红素、总胆红素（TBil）和谷丙转氨酶（ALT）为显著的代谢指标。此外，糖类抗原125（CA125）和人附睾蛋白4（HE4）为显著的协变量。RCS分析显示大多数代谢指标与结局指标之间存在非线性关联。ROC曲线分析表明，谷丙转氨酶（ALT）的曲线下面积（AUC）大于0.6。
ALT与子宫内膜异位症严重程度呈负相关，是具有统计学意义的独立影响因素。这一发现可为临床医生提供用于疾病早期检测和精确监测疾病进展的非侵入性生物标志物。
