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进展期胃癌病人发生腹腔脱落细胞学阳性的危险因素分析及风险预测评分模型建立
引用本文:丁平安,杨沛刚,田园,林叶成,郭洪海,刘洋,张志栋,王冬,李勇,赵群. 进展期胃癌病人发生腹腔脱落细胞学阳性的危险因素分析及风险预测评分模型建立[J]. 腹部外科, 2021, 34(1): 34-39
作者姓名:丁平安  杨沛刚  田园  林叶成  郭洪海  刘洋  张志栋  王冬  李勇  赵群
作者单位:河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011;河北医科大学第四医院外三科,河北石家庄050011
基金项目:河北卫健委县级公立医院适宜卫生技术推广入库项目(2019024);政府资助临床医学优秀人才培养项目(2019012)。
摘    要:目的 探讨影响进展期胃癌病人腹腔脱落细胞学阳性的危险因素,建立腹腔脱落细胞学阳性的风险预测评分模型.方法 收集分析河北医科大学第四医院2012年2月至2018年12月期间开展的一项前瞻性、多中心、开放、随机对照Ⅲ期临床试验(NCT01516944)中的225例进展期胃癌病人临床病理资料,所有病人术中均行腹腔镜探查及腹腔...

关 键 词:进展期胃癌  脱落细胞学  危险因素  风险预测模型

Clinicopathological factors affecting cytologically positive peritoneal exfoliation in advanced gastric cancer
Ding Ping′an,Yang Peigang,Tian Yuan,Lin Yechen,Guo Honghai,Liu Yang,Zhang Zhidong,Wang Dong,Li Yong,Zhao Qun. Clinicopathological factors affecting cytologically positive peritoneal exfoliation in advanced gastric cancer[J]. Journal of Abdominal Surgery, 2021, 34(1): 34-39
Authors:Ding Ping′an  Yang Peigang  Tian Yuan  Lin Yechen  Guo Honghai  Liu Yang  Zhang Zhidong  Wang Dong  Li Yong  Zhao Qun
Affiliation:(DepartmentⅢof Surgery,Fourth Hospital,Hebei Medical University,Hebei Shijiazhuang 050011,China)
Abstract:Objective To explore the risk factors for positive peritoneal abscission cytology in patients with advanced gastric cancer and establish a risk prediction scoring model for positive peritoneal abscission cytology.Methods From February 2012 to December 2018,clinicopathological data were reviewed for 225 patients with advanced gastric cancer in a prospective,multi-center,open,randomized controlled phaseⅢclinical trial(NCT01516944).Microscopic intraoperative exploration of abdominal cavity and peritoneal exfoliation cytology(500 mL normal saline flushing)were performed to detect the positive rate of peritoneal exfoliated cancer cells.And clinicopathological factors affecting the positive peritoneal exfoliation cytology were examined.Results Positive exfoliation cytology had a positive rate of 14.22%in peritoneal washing fluid.Univariate analysis revealed that patient age,tumor diameter,depth of invasion(cT stage),histological type,tumor location,lymph node metastasis(cN stage),serum tumor marker carcinoembryonic antigen(CEA),cancer antigen 72-4(CA72-4)and cancer antigen 19-9(CA19-9)were all risk factors for positive abdominal exfoliation cytology(P<0.05);multivariate analysis indicated that depth of tumor invasion was cT4a-cT4b stage[OR=20.954,95%confidence interval(CI)(1.610,12.651),P=0.020],CEA[OR=7.695,95%CI(1.307,8.669),P=0.001],CA72-4[OR=7.551,95%CI(2.255,25.283),P=0.001]and CA19-9[OR=3.317,95%CI(1.011,10.883),P=0.048]affected independent risk factors for positive abdominal exfoliation cytology.The risk prediction equation was established on the basis of the results of multivariate Logistic regression:logit(p)=-7.088+3.042×X1+2.041×X2+1.199×X3+2.022×X4 and Hosmer-Lemeshow test was utilized for detecting the goodness-of-fit of regression equation(P=0.614).ROC curve was employed for evaluating the discrimination of regression equation.The area under the curve was 0.844[95%CI(0.751,0.936),P=0.000].The preoperative tumor infiltration depth was cT4a-cT4b,CEA,CA72-4 and CA19-9 were positive and the positive risk scores of abdominal exfoliation were 3,2,2 and 1.The probability of positive abdominal exfoliation cytology was 19.44%in patients with 4 points and 4.94%in those with scores<4 points.Conclusion The elevated levels of CEA,CA72-4 and CA19-9 in patients with advanced gastric cancer and the degree of infiltration in cT4a-cT4b stage suggest that there may be a positive cytology for abdominal abscission.At the same time,the above-mentioned indicators are utilized for establishing a risk scoring model for effectively predicting high-risk patients with positive peritoneal cytology in the development of gastric cancer.
Keywords:Advanced gastric cancer  Shedding cytology  Risk factors  Risk prediction model
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