Li Lian, Tian Jing, Zhang Liwen, Liu Luyang, Sheng Chao, Huang Yubei, Zheng Hong, Song Fengju, Chen Kexin
Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Department of Urology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
J Cancer. 2021 Mar 5;12(9):2687-2693. doi: 10.7150/jca.51642. eCollection 2021.
Inflammatory markers have been reported to be predictors for the presence of epithelial ovarian cancer (EOC), however, the cut-off value of each marker remains unclear and predictive capability of the markers in different histology types of EOC is still unknown. A total of 207 patients with benign ovarian masses and 887 EOC patients who underwent surgical resection, and were pathologically diagnosed were included. We compared the difference of preoperative inflammatory markers between benign ovarian masses and EOC patients. Stratified analysis by histology subtype was further conducted. Logistic regression analyses and receiver operating characteristic (ROC) curves was used to evaluate the predictive capability of the markers. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) were significantly associated with all stages and subtypes of EOC (P<0.001). The optimal cut-off points based on ROC curve analyses for NLR, PLR, and LMR were found to be 2.139 (AUC=0.749, <0.001), 182.698 (AUC=0.730, <0.001), and 3.619 (AUC = 0.709, <0.001), respectively. In low CA125 level patients, high level of NLR and PLR increase the risk of endometrioid EOC, while low level of LMR were significantly associated with an increased risk of serous EOC. In addition to CA125, NLR, PLR, and LMR could be used as predictors of EOC and preoperative inflammatory markers may be used as a potential biomarker for predicting different histotypes of EOC.
炎症标志物已被报道为上皮性卵巢癌(EOC)存在的预测指标,然而,每种标志物的临界值仍不明确,且这些标志物在不同组织学类型的EOC中的预测能力尚不清楚。本研究纳入了207例接受手术切除并经病理诊断的卵巢良性肿块患者和887例EOC患者。我们比较了卵巢良性肿块患者和EOC患者术前炎症标志物的差异。进一步按组织学亚型进行分层分析。采用逻辑回归分析和受试者工作特征(ROC)曲线来评估这些标志物的预测能力。中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)和淋巴细胞与单核细胞比值(LMR)与EOC的所有分期和亚型均显著相关(P<0.001)。基于ROC曲线分析,发现NLR、PLR和LMR的最佳临界点分别为2.139(AUC=0.749,<0.001)、182.698(AUC=0.730,<0.001)和3.619(AUC = 0.709,<0.001)。在CA125水平较低的患者中,高水平的NLR和PLR会增加子宫内膜样EOC的风险,而低水平的LMR与浆液性EOC风险增加显著相关。除CA125外,NLR、PLR和LMR可作为EOC的预测指标,术前炎症标志物可能作为预测不同组织学类型EOC的潜在生物标志物。