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Title: [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].
Author: Liu Q, Peng J, Jiang HG, Wang WB, Dai J, Zhou FX.
Journal: Zhonghua Zhong Liu Za Zhi; 2019 Aug 23; 41(8):599-603. PubMed ID: 31434451.
Abstract:
Objective: 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. Methods: 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. Results: Compared with pN0 group, NE (P=0.022), CRP (P<0.001), NLR (P<0.001), PLR (P=0.003) and CAR (P<0.001) were higher, LY (P=0.003) and Alb (P=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 P<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. OR were 8.084, 3.540 and 3.092, respectively (all P<0.05). The C-index of the nomogram model was 0.847 (95% CI: 0.782-0.915). The predicting calibration curve was properly fit with the ideal curve in calibration chart. Conclusion: 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. 目的： 探讨术前中性粒细胞/淋巴细胞比值(NLR)、C反应蛋白/白蛋白比值(CAR)等系统性炎症反应指标与cN0胃癌患者淋巴结转移的关系，并建立预测cN0胃癌患者淋巴结转移风险的列线图模型。 方法： 回顾性分析134例cN0胃癌患者的术前系统性炎症指标及临床病理资料，比较术后病理诊断无淋巴结转移(pN0)组和淋巴结转移阳性(pN＋)组患者的术前系统性炎症指标。采用受试者工作特征(ROC)曲线评估术前系统性炎症指标对淋巴结转移的预测效能，采用单因素分析和多因素Logistic回归分析方法分析淋巴结转移的影响因素，应用R软件建立列线图预测模型，以Bootstrap法进行内部验证。 结果： pN＋组与pN0组比较，中性粒细胞计数(P＝0.022)、C反应蛋白(P<0.001)、NLR(P<0.001)、血小板/淋巴细胞比值(PLR, P＝0.003)和CAR(P<0.001)增高，淋巴细胞计数(P＝0.003)和Alb(P＝0.042)降低。ROC曲线分析显示，NLR、PLR和CAR诊断cN0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，最佳界值分别为2.12、113.59和0.02，相应的灵敏度和特异度分别为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胃癌患者淋巴结转移有关(均P<0.05)。多因素分析显示，浸润深度、NLR和CAR是cN0胃癌患者淋巴结转移的独立影响因素，OR分别为8.084、3.540和3.092(均P<0.05)。列线图预测模型的C－index为0.847(95% CI：0.782～0.915)，校准图中的校准预测曲线与理想曲线贴合良好。 结论： 结合NLR、CAR构建的列线图模型符合度良好，可较准确预测cN0胃癌患者的淋巴结转移风险。.

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