早期胃癌淋巴结转移的相关危险因素分析及预测模型的建立

Analysis of risk factors and establishment of predictive model for lymph node metastasis in early gastric cancer

目的探索早期胃癌(early gastric cancer,EGC)淋巴结转移的规律及与其相关的危险因素,建立列线图模型,并评估其对淋巴结转移的预测价值。方法选取2010年1月至2019年12月西安交通大学第二附属医院普外科就诊并行手术治疗的EGC患者为研究对象,比较淋巴结转移阳性组和阴性组的临床病理特征,采用多因素Logistic回归分析选择变量构建列线图预测模型,通过内部验证评估其预测性能。结果共收集EGC患者304例,其中发生淋巴结转移者40例。单因素分析显示,两组在性别、吸烟史、组织学特征、分化程度、病变特征(发红、周围黏膜隆起)、浸润深度、病变长径、伴萎缩方面比较,差异有统计学意义(P<0.05)。多因素分析显示,黏膜下层浸润(OR=3.427)、组织学混合型(OR_(M)=36.407,OR_(PUD)=4.966)、未分化型(OR=7.38)是EGC患者淋巴结转移的独立危险因素(P<0.05)。相比分化程度,以组织学分型联合浸润深度建立的预测模型诊断性能较好。在此基础上建立的预测EGC淋巴结转移风险的列线图模型,经Bootstrap自抽样进行内部验证,模型的C-index值为0.804,校正曲线显示,预测淋巴结转移率与实际淋巴结转移发生率的相关性良好。结论以浸润深度、组织学为基础建立的相关列线图预测模型对EGC淋巴结转移有较好的预测性能,具备一定的临床参考价值。

Objective To explore the regularity of lymph node metastasis in early gastric cancer(EGC)and its related risk factors,to establish a nomogram model,and to evaluate its predictive value for lymph node metasta.MethodsIn this study,all patients with EGC who received surgical treatment in the Second Affiliated Hospital of Xi’an Jiaotong University from Jan.2010 to Dec.2019 were selected as subjects.The clinicopathological features of lymph node metastasis(+)and lymph node metastasis(-)were compared.Multivariate Logistic regression analysis was used to select variables to construct a line chart prediction model,and its prediction performance was evaluated by internal verification.Results A total of 304 cases of EGC were collected,of which 40 had lymph node metastasis.The comparison between lymph node metastasis(+)and lymph node metastasis(-)showed that there were statistically significant differences between them in terms of sex,smoking history,histological features,degree of differentiation,lesion characteristics(redness,peripheral mucosal eminence),depth of invasion,lesion length and atrophy(P<0.05).Multivariate Logistic regression analysis found that submucosal infiltration(OR=3.427),mixed histology(OR_(M)=36.407,OR_(PUD)=4.966)and undifferentiated(OR=7.38)were independent risk factors for lymph node metastasis in EGC(P<0.05).Compared with the degree of differentiation,the predictive model established by histological classification and infiltration depth had better diagnostic performance.On this basis,the nomogram model for predicting the risk of lymph node metastasis in EGC was verified by Bootstrap self-sampling,and the C-index value of the model was 0.804.The calibration curve showed that the correlation between the predicted and the actual incidence of lymph node metastasis was good.Conclusion The nomogram prediction model based on the depth of invasion and histology has a good performance in predicting lymph node metastasis of EGC and has a certain clinical reference value.