子宫内膜异位症
医学
接收机工作特性
逻辑回归
胃肠病学
内科学
淋巴细胞
曲线下面积
血红蛋白
恶性肿瘤
癌抗原
混淆
外周血淋巴细胞
外周血
癌症
作者
Ting Chen,Jia‐Ling Wei,Ting Leng,Fei Gao,Shunyu Hou
摘要
We aimed to analyze the differences in the peripheral blood cells and tumor biomarkers between the patients with endometriosis and healthy people, and establish a more efficient combined diagnostic model.We retrospectively analyzed the differences in the peripheral blood cells and tumor biomarkers between the patients with endometriosis and healthy people. Binary logistic regression analysis was used to establish a combined diagnostic model. We plotted the receiver operator characteristic (ROC) curve to analyze the diagnostic efficiency of different diagnostic indexes.Compared with patients in the control group, patients in the endometriosis group had significantly lower eosinophil% (p = 0.045), neutrophil (p = 0.001), lymphocyte (p < 0.001), red blood cells (RBCs) (p < 0.001), and hemoglobin (HGB) (p < 0.001), and had significantly higher monocyte% (p = 0.008), monocyte-to-lymphocyte ratio (MLR) (p = 0.001), platelet-to-lymphocyte ratio (PLR) (p < 0.001), carbohydrate antigen (CA)-199 (p < 0.001), CA125 (p < 0.001), human epididymis protein (HE)-4 (p < 0.001), and the risk of ovarian malignancy algorithm (ROMA) (p < 0.001). The combined diagnostic model of HGB, CA199, CA125, and HE4 was established by binary logistic regression analysis. The ROC curve showed that the combined diagnostic model reached a sensitivity of 85.4%, a specificity of 78.83%, and an area under the curve of 0.900, which was significantly higher than that of the individual index in endometriosis diagnosis.The combined diagnostic model of HGB, CA199, CA125, and HE4 may provide a new approach for the early non-invasive diagnosis of endometriosis.
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