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[基于术前C反应蛋白/白蛋白比值联合建立预测cN0期胃癌患者淋巴结转移的列线图模型]

[Establishment of a nomogram model for predicting lymph node metastasis in patients with cN0 gastric cancer based on combination of preoperative C-reactive protein/albumin ratio].

作者信息

Liu Q, Peng J, Jiang H G, Wang W B, Dai J, Zhou F X

机构信息

Department of Radiation Oncology and Medical Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, Wuhan 430071, China.

出版信息

Zhonghua Zhong Liu Za Zhi. 2019 Aug 23;41(8):599-603. doi: 10.3760/cma.j.issn.0253-3766.2019.08.008.

Abstract

To investigate the relationship between systemic inflammatory markers such as neutrophil/lymphocyte ratio (NLR) and C-reactive protein/albumin ratio (CAR), and lymph node metastasis in patients with cN0 gastric cancer. To establish a nomogram model to predict the risk of lymph node metastasis in patients with cN0 gastric cancer. The preoperative systemic inflammatory markers and clinical data of 134 patients with cN0 gastric cancer were retrospectively analyzed, and these markers of patients with negative (pN0) or positive (pN+ ) lymph node metastasis in postoperative pathological diagnosis were compared. The receiver operating characteristic (ROC) curve was used to evaluate the predictive effect of preoperative systemic inflammatory markers on lymph node metastasis. The influencing factors for lymph node metastasis were assessed by univariate analysis and multivariate logistic regression analysis. A nomogram subsequently established by R software was validated by Bootstrap resampling as internal validation. Compared with pN0 group, NE (=0.022), CRP (<0.001), NLR (<0.001), PLR (=0.003) and CAR (<0.001) were higher, LY (=0.003) and Alb (=0.042) were lower in pN+ group. ROC curve analysis showed that the area under the curve (AUC) of postoperative pathological lymph node metastasis in patients with cN0 gastric cancer diagnosed by NLR, PLR and CAR were 0.687, 0.651 and 0.694, respectively, and the best cutoff values were 2.12, 113.59 and 0.02, respectively. The corresponding sensitivity and specificity were 62.9% and 72.2%, 77.4% and 48.6%, 74.2% and 58.3%, respectively. Univariate analysis showed that tumor size, depth of invasion, NLR, PLR and CAR were associated with lymph node metastasis in cN0 gastric cancer patients (all <0.05). Multivariate analysis showed that depth of invasion, NLR and CAR were independent influencing factors of lymph node metastasis in patients with cN0 gastric cancer. were 8.084, 3.540 and 3.092, respectively (all <0.05). The C-index of the nomogram model was 0.847 (95% 0.782-0.915). The predicting calibration curve was properly fit with the ideal curve in calibration chart. Combination of NLR and CAR to establish a nomogram model has a good consistency and can accurately predict the risk of lymph node metastasis in patients with cN0 gastric cancer.

摘要

探讨中性粒细胞/淋巴细胞比值(NLR)、C反应蛋白/白蛋白比值(CAR)等全身炎症标志物与cN0期胃癌患者淋巴结转移之间的关系。建立列线图模型以预测cN0期胃癌患者淋巴结转移风险。回顾性分析134例cN0期胃癌患者的术前全身炎症标志物及临床资料,并比较术后病理诊断为淋巴结转移阴性(pN0)或阳性(pN+)患者的这些标志物。采用受试者工作特征(ROC)曲线评估术前全身炎症标志物对淋巴结转移的预测效果。通过单因素分析和多因素logistic回归分析评估淋巴结转移的影响因素。随后用R软件建立的列线图经Bootstrap重抽样法进行内部验证。与pN0组相比,pN+组中性粒细胞计数(NE,=0.022)、C反应蛋白(CRP,<0.001)、NLR(<0.001)、血小板/淋巴细胞比值(PLR,=0.003)和CAR(<0.001)较高,淋巴细胞计数(LY,=0.003)和白蛋白(Alb,=0.042)较低。ROC曲线分析显示,NLR、PLR和CAR诊断的cN0期胃癌患者术后病理淋巴结转移的曲线下面积(AUC)分别为0.687、0.651和0.694,最佳截断值分别为2.12、113.59和0.02。相应的敏感度和特异度分别为62.9%和72.2%、77.4%和48.6%、74.2%和58.3%。单因素分析显示,肿瘤大小、浸润深度、NLR、PLR和CAR与cN0期胃癌患者淋巴结转移有关(均<0.05)。多因素分析显示,浸润深度、NLR和CAR是cN0期胃癌患者淋巴结转移的独立影响因素,其比值比分别为8.084、3.540和3.092(均<0.05)。列线图模型的C指数为0.847(95%可信区间0.782 - 0.915)。预测校准曲线与校准图中的理想曲线拟合良好。联合NLR和CAR建立的列线图模型具有良好的一致性,能够准确预测cN0期胃癌患者淋巴结转移风险。

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