Wang Wei, Nie Runcong, Zhou Zhiwei
Department of Gastric Surgery, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Zhonghua Wei Chang Wai Ke Za Zhi. 2018 May 25;21(5):541-545.
To explore the risk factors and establish an effective model to predict lymph node metastasis (LNM) for remnant gastric cancer (RGC).
Clinicopathological characteristics of 91 RGC patients undergoing radical gastrectomy at Sun Yat-sen University Cancer Center from January 2000 to December 2017 were retrospectively analyzed. RGC was defined as cancer detected in the remnant stomach >5 years for primary benign diseases or >10 years for malignant diseases following distal gastrectomy. Risk factors of LNM in RGC were identified using logistic regression (P<0.1). Covariates were then scored according to the β regression coefficient in the multivariate analysis, and a score model was established, in which higher score indicated higher risk of LNM. Finally, receiver operating characteristic(ROC) curve was used to evaluate the diagnostic efficacy of risk factors and the score model.
Among the 91 RGC patients, 84 were male and 7 were female with the age ranging from 47 to 82 years (63.7±8.5) years. Mean harvested lymph node (LN) was 16.0±11.8, including ≥15 LNs in 42(46.2%) patients and <15 LNs in 49(53.8%) patients. Forty-six (50.5%) patients were identified as LNM. Univariate analysis showed that tumor size ≥4 cm (χ=8.106, P=0.004), Borrmann III(-IIII( gross type (χ=6.129, P=0.013), increased CEA level (χ=4.041, P=0.044) and T3-4 stage (χ=17.321, P=0.000) were associated with LNM in RGC. In Logistic multivariate analysis, tumor size ≥4 cm (OR: 2.362, 95%CI: 0.829-6.730, P=0.100, β regression coefficient: 0.859) and T3-4 stage (OR: 7.914, 95%CI: 1.956-32.017, P=0.004, β regression coefficient: 2.069) remained as the independent risk factors for LNM, and were scored as 1 and 2 point in the final prediction model. In the final score model, LNM of patients with 0, 1, 2, 3 point were 11.1%(2/18), 1/5, 51.6%(16/31) and 73.0%(27/37), respectively. The AUC of the prediction model was 0.756 (P=0.000).
Increased CEA level, tumor size ≥4 cm, Borrmann III(-IIII( gross type, and deeper T stage are associated with LNM in RGC. Moreover, the score model combining with tumor size and T stage can effectively predict the LNM in RGC.
探讨残胃癌（RGC）淋巴结转移（LNM）的危险因素并建立有效的预测模型。
回顾性分析2000年1月至2017年12月在中山大学肿瘤防治中心接受根治性胃切除术的91例RGC患者的临床病理特征。RGC定义为在远端胃切除术后，因原发性良性疾病胃残端发现癌症>5年或因恶性疾病>10年。采用逻辑回归分析（P<0.1）确定RGC中LNM的危险因素。然后根据多变量分析中的β回归系数对协变量进行评分，并建立评分模型，其中评分越高表明LNM风险越高。最后，采用受试者工作特征（ROC）曲线评估危险因素和评分模型的诊断效能。
91例RGC患者中，男性84例，女性7例，年龄4782岁，平均（63.7±8.5）岁。平均清扫淋巴结（LN）数为16.0±11.8枚，其中≥15枚LN者42例（46.2%），<15枚LN者49例（53.8%）。46例（50.5%）患者发生LNM。单因素分析显示，肿瘤大小≥4 cm（χ=8.106，P=0.004）、Borrmann III型（χ=6.129，P=0.013）、癌胚抗原（CEA）水平升高（χ=4.041，P=0.044）及T3-4期（χ=17.321，P=0.000）与RGC的LNM相关。逻辑多因素分析显示，肿瘤大小≥4 cm（OR：2.362，95%CI：0.8296.730，P=0.100，β回归系数：0.859）和T3-4期（OR：7.914，95%CI：1.956~32.017，P=0.004，β回归系数：2.069）仍是LNM的独立危险因素，在最终预测模型中分别计1分和2分。在最终评分模型中，0分、1分、2分、3分患者的LNM发生率分别为11.1%（2/18）、1/5、51.6%（16/31）和73.0%（27/37）。预测模型的曲线下面积（AUC）为0.756（P=0.000）。
CEA水平升高、肿瘤大小≥4 cm、Borrmann III型及T分期加深与RGC的LNM相关。此外，结合肿瘤大小和T分期的评分模型可有效预测RGC的LNM。
