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中华普外科手术学杂志(电子版) ›› 2024, Vol. 18 ›› Issue (06) : 694 -699. doi: 10.3877/cma.j.issn.1674-3946.2024.06.027

论著

胃癌脾门淋巴结转移危险因素
贺斌1, 马晋峰2,()   
  1. 1. 030001 太原,山西医科大学研究生院
    2. 030001 太原,山西省肿瘤医院,中国医学科学院肿瘤医院山西医院,山西医科大学附属肿瘤医院
  • 收稿日期:2023-11-10 出版日期:2029-12-26
  • 通信作者: 马晋峰

Risk factors for splenic hilar lymph node metastasis in gastric cancer

Bin He1, Jinfeng Ma2,()   

  1. 1. Graduate college of Shaanxi Medical University, Taiyuan Shaanxi Province 030001, China
    2. Shaanxi Cancer Hospital, Shaanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shaanxi Medical University Taiyuan Shaanxi Province 030001, China
  • Received:2023-11-10 Published:2029-12-26
  • Corresponding author: Jinfeng Ma
  • Supported by:
    Central Guided Local Science and Technology Development Funding Program, Construction of a platform for drug resistance mechanism and clinical diagnosis and treatment of gastric cancer in Shanxi Province, China(YDZJSX2022B014)
引用本文:

贺斌, 马晋峰. 胃癌脾门淋巴结转移危险因素[J/OL]. 中华普外科手术学杂志(电子版), 2024, 18(06): 694-699.

Bin He, Jinfeng Ma. Risk factors for splenic hilar lymph node metastasis in gastric cancer[J/OL]. Chinese Journal of Operative Procedures of General Surgery(Electronic Edition), 2024, 18(06): 694-699.

目的

探讨胃癌患者脾门淋巴结转移危险因素。

方法

回顾性分析2020年1月至2022年1月150例胃上部癌患者临床资料。使用免疫组织化学方法检测淋巴结转移或微转移。采用SPSS 20.0软件进行数据分析,计量资料用()表示,采用独立样本t检验;计数资料用频数表示,采用χ2检验;用多因素Logistic回归分别分析影响脾门淋巴结转移、微转移及总体转移的独立因素;采用EmpowerStats软件中的分层交互检验作用分析性别对独立因素与脾门淋巴结转移关系的影响作用;基于筛选的重要影响因素构建脾门淋巴结转移的结构方程模型并进行分析和检验。P<0.05为差异有统计学意义。

结果

150例患者中,33例患者脾门淋巴结转移,转移率为22.0 %(33/150),常规病理阴性的117例患者中有38例有脾门淋巴结微转移,转移率为32.5 %(38/117)。总体转移率为47.3%(71/150)。肿瘤横向部位、Bormann分型、No.4sa淋巴结转移、TNM分期、浸润深度、No.2淋巴结转移、No.4sb淋巴结转移是脾门淋巴结总体转移的独立影响因素(P<0.05)。进一步基于以上高危因素构建影响淋巴结总体转移的结构方程模型,可有效反映各研究变量与淋巴结总体转移的关系。验证模型具有较好的区分度、准确度。

结论

大弯侧、No.4sa淋巴结转移、Bormann分型Ⅲ-Ⅳ型、No.4sb淋巴结转移、黏膜下层浸润、Ⅲ-Ⅳ期、No.2淋巴结转移是脾门淋巴结总体转移的独立因素。本研究构建的影响淋巴结总体转移的结构方程模型整体适配情况较优,且验证模型具有较好的区分度、准确度。

Objective

To investigate the risk factors of splenic hilar lymph node metastasis in patients with gastric cancer.

Methods

The clinical data of 150 patients with upper gastric cancer from January 2020 to January 2022 were retrospectively analyzed. Lymph node metastases or micrometastases were detected by immunohistochemical methods. SPSS 20.0 was used for data analysis. Measurement data were expressed as () and independent sample t test was used. The counting data were expressed by frequency and χ2 test was used. Multivariate Logistic regression was used to analyze the independent factors affecting hilar lymph node metastasis, micrometastasis and total metastasis. The influence of gender on the relationship between independent factors and hilar lymph node metastasis was analyzed using the layered interaction test in Empower Stats software. The structural equation model of hilar lymph node metastasis was constructed based on the important factors of screening and analyzed and tested. P<0.05 was considered statistically significant.

Results

Among the 150 patients, 33 patients had hilar lymph node metastasis, with a metastasis rate of 22.0% (33/150). Among the 117 patients with negative routine pathology, 38 patients had hilar lymph node micrometastasis, with a metastasis rate of 32.5% (38/117). The overall transfer rate was 47.3% (71/150). Transverse location of tumor, Bormann classification, No.4sa lymph node metastasis, TNM stage, depth of invasion, No.2 lymph node metastasis and No.4sb lymph node metastasis were independent factors of total hilar lymph node metastasis (P<0.05). Based on the above risk factors, the structural equation model affecting the overall lymph node metastasis was further constructed, which could effectively reflect the relationship between the study variables and the overall lymph node metastasis. The verification model has good differentiation and accuracy.

Conclusion

Major curved side, No.4sa lymph node metastasis, Bormann classification Ⅲ-Ⅳ, No.4sb lymph node metastasis, submucosal infiltration, Ⅲ-Ⅳ stage, No.2 lymph node metastasis were independent factors of total hilar lymph node metastasis. In this study, the structural equation model established to affect the overall lymph node metastasis has a good overall fit, and the verified model has a good degree of differentiation and accuracy.

图1 110例胃上癌患者行根治性胃癌D2淋巴结清扫术的淋巴结分布[6] 注:A=胃周各站淋巴结分布;B=脾门淋巴结分布。
图2 脾门淋巴结HE染色显示转移阳性(400×)
图3 脾门淋巴结微转移阴性 注:A=脾门淋巴结HE染色未见转移(200×);B=对应脾门淋巴结CK19阴性表达(200×);C=对应脾门淋巴结CK20阴性表达(200×)。
图4 脾门淋巴结微转移阳性 注:A=脾门淋巴结HE染色未见转移(200×);B=对应脾门淋巴结CK19阳性表达(200×);C=对应脾门淋巴结CK20阳性表达(200×)。
表1 脾门淋巴结转移与临床资料的关系(例)
表2 脾门淋巴结转移与相关淋巴结状态的关系(例)
表3 多因素Logistic回归分析
表4 分层交互分析性别对高危因素与脾门淋巴结转移关系的影响作用
性别模型 男性 女性 P
β(95%CI P β(95%CI P
肿瘤横向部位 未调整 3.236(0.983-6.796) 0.021 2.195(-2.736-3.987) 0.064 0.375
模型1 22.536(5.475-38.924) 0.007 3.175(-1.246-9.638) 0.083 0.284
模型2 5.893(2.435-19.207) 0.015 2.295(-1.284-6.938) 0.092 0.136
TNM分期 未调整 4.193(1.474-9.225) 0.023 10.675(-3.784-22.763) 0.163 0.453
模型1 28.752(11.845-35.978) 0.011 7.649(-3.457-11.938) 0.057 0.098
模型2 15.233(7.475-24.893) 0.018 2.133(-0.958-5.946) 0.061 0.147
Bormann分型 未调整 5.274(1.135-7.284) 0.024 6.827(-1.498-17.438) 0.082 0.233
模型1 3.122(1.285-7.243) 0.036 3.926(-0.875-8.045) 0.079 0.295
模型2 12.477(5.281-23.476) 0.042 12.346(-2.458-20.936) 0.073 0.167
浸润深度 未调整 9.835(1.472-18.753) 0.005 5.233(-0.872~8.725) 0.064 0.294
模型1 2.247(1.046-7.890) 0.037 2.136(-0.451-6.238) 0.082 0.463
模型2 13.146(2.794-38.904) 0.022 7.231(-2.454-10.627) 0.095 0.128
No.2淋巴结转移 未调整 3.236(1.983-6.796) 0.014 12.465(-7.243-23.579) 0.086 0.135
模型1 4.578(1.233-9.835) 0.020 8.238(-1.925-15.690) 0.057 0.349
模型2 5.893(1.946-11.422) 0.041 5.237(-0.852-9.456) 0.094 0.073
No.4sa淋巴结转移 未调整 2.784(1.625-5.238) 0.038 11.824(-3.167-19.767) 0.088 0.085
模型1 3.964(1.247-10.536) 0.027 2.976(-0.763-5.864) 0.065 0.384
模型2 8.492(2.490-12.678) 0.033 3.142(-1.237-6.235) 0.052 0.375
No.4sb淋巴结转移 未调整 5.237(1.244-7.905) 0.025 2.679(-0.923-7.146) 0.051 0.276
模型1 4.157(1.238-9.367) 0.019 4.286(-1.317-9.365) 0.112 0.124
模型2 6.305(1.559-15.371) 0.022 4.391(2.067-10.339) 0.106 0.193
表5 结构方程模型拟合指标
图5 分析脾门淋巴结转移的结构方程模型
表6 脾门淋巴结转移结构方程模型参数
表7 收敛效度和组合信度检验
表8 区分效度检验
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