作者：穆艾太尔·麦提努日，马乐，叶建蔚，郑超，毛睿，玛依努尔·艾力

单位：新疆医科大学第一附属医院 肿瘤中心肿瘤三科， 新疆 乌鲁木齐 830000

Authors: Muaitaier Maitinuri，Ma Le，Ye Jianwei，Zheng Chao，Mao Rui，Mayinuer Aili

Unit: Department 3 of Cancer Center，First Affiliated Hospital of Xinjiang Medical University，Urumqi 830000，Xinjiang，China

摘要：

目的 探讨结合炎症指标的临床评分模型对食管癌患者术后生存情况的预测价值。方法 选取2014年1月至2016年12月在新疆医科大学第一附属医院行手术治疗并且病理确诊的食管癌患者161例，分别以食管癌患者术后5年内出现肿瘤复发转移和死亡作为因变量，各临床病理指标作为自变量，采用Cox单因素和多因素分析获得影响食管癌患者术后肿瘤复发转移和死亡的独立预测因素，绘制各独立因素预测食管癌患者术后生存情况的ROC曲线，根据独立预测因素建立联合预测系统和临床评分模型，并绘制相应ROC曲线进行分析。结果 本研究共纳入161例接受手术治疗的食管癌患者，平均年龄（54.2±11.5）岁，其中男性112例（69.5%），女性49例（30.5%），术后1年、3年、5年无病生存率和总生存率分别为62.5%、41.5%、28.7%和78.2%、58.4%、40.1%。Cox单因素分析结果显示，吸烟史、饮酒史、肿瘤直径、肿瘤浸润深度、淋巴结转移、中性粒细胞和淋巴细胞比值（NLR）以及血小板和淋巴细胞比值（PLR）在单因素分析中具有统计学意义（P<0.05）。校正和控制混杂变量后，肿瘤直径、肿瘤浸润深度、淋巴结转移以及NLR为影响食管癌患者术后无病生存期和总生存期的独立预测因素（P<0.05）。联合4个指标绘制预测患者术后肿瘤复发转移和死亡的ROC曲线，对应的AUC分别为0.773(0.741～0.812)和0.794(0.758～0.837)，其敏感度和特异度分别为82.4%、76.5%和78.9%、79.5%。根据临床评分模型预测患者术后肿瘤复发转移和死亡的ROC曲线显示，评分>2分为预测患者术后肿瘤复发转移和死亡的最佳诊断截点，AUC分别为0.845 (0.812～0.889)和0.883 (0.841～0.927)，其敏感度和特异度分别为87.3%、82.5%和88.3%、83.4%。结论 结合肿瘤直径、肿瘤浸润深度、淋巴结转移以及NLR的临床评分模型能准确预测食管癌患者术后生存情况。 

关键词：炎症指标； 临床评分模型； 食管癌； 生存情况

Abstract：

Objective To explore the value of clinical scoring model combined with inflammatory indexes in predicting postoperative survival of patients with esophageal cancer. Method 161 patients with esophageal cancer who underwent surgical treatment in our hospital from January 2014 to December 2016 and were pathologically confirmed were included as the study subjects. Taking the recurrence ，metastasis and death of esophageal cancer patients within 5 years after operation as the dependent variable，each clinicopathological index as the independent variable，Cox univariate and multivariate analysis were used to obtain the independent predictors of affecting recurrence，metastasis and death of esophageal cancer patients，and draw the ROC curve of each independent factor to predict the postoperative survival of esophageal cancer patients. According to the independent predictors，the joint prediction system and clinical scoring model were established，and the corresponding ROC curve was drawn for analysis. Result A total of 161 patients with esophageal cancer were included in this study. The average age was （54.2±11.5） years， including 112 males （69.5%） and 49 females （30.5%）. The disease-free survival rate and overall survival rate at 1， 3 and 5 years were 62.5%， 41.5%， 28.7% and 78.2%， 58.4% and 40.1% respectively. Cox univariate analysis showed that smoking history， drinking history， tumor diameter， tumor invasion depth， lymph node metastasis， neutrophil to lymphocyte ratio （NLR） and platelet to lymphocyte ratio （PLR） were statistically significant in univariate analysis（P<0.05）. After adjusting and controlling for confounding variables， tumor diameter， tumor invasion depth， lymph node metastasis and NLR were independent predictors of disease -free survival and overall survival in patients with esophageal cancer （P <0.05）. The ROC curves for predicting postoperative tumor recurrence， metastasis and death were drawn by combining four indexes. The corresponding AUCs were 0.773 （0.741-0.812） and 0.794 （0.758-0.837）， respectively. The sensitivity and specificity were 82.4%，76.5% and 78.9% and 79.5% respectively. According to the ROC curve of clinical scoring model to predict postoperative tumor recurrence， metastasis and death， when the score >2 was the best diagnostic cut -off point for predicting postoperative tumor recurrence metastasis and death， the AUC was 0.845（0.812-0.889）and 0.883（0.841-0.927）， and its sensitivity and specificity were 87.3%， 82.5% and 88.3%， 83.4% respectively. Conclusion The clinical scoring model combined with tumor diameter, tumor invasion depth, lymph node metastasis and NLR can accurately predict the postoperative survival of patients with esophageal cancer.

Key Words: Inflammatory indexes; Clinical scoring model; Esophageal cancer; Survival