Ting Chen1,2, Jia-Ling Wei1,2, Ting Leng1,2, Fei Gao1,2, Shun-Yu Hou1,2. 1. The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China. 2. Suzhou Municipal Hospital, Suzhou, China.
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: The combined diagnostic model of HGB, CA199, CA125, and HE4 may provide a new approach for the early non-invasive diagnosis of endometriosis.
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: The combined diagnostic model of HGB, CA199, CA125, and HE4 may provide a new approach for the early non-invasive diagnosis of endometriosis.
Authors: Ignacio Zapardiel; Mikel Gorostidi; Antonella Ravaggi; Maria T Allende; Margarida Silveira; Daniel Abehsera; Ronalds Macuks Journal: Int J Gynecol Cancer Date: 2016-01 Impact factor: 3.437
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