Model to identify early-stage gastric cancers with deep invasion of submucosa based on endoscopy and endoscopic ultrasonography findings

被引:29
作者
Cheng, Jieyao [1 ]
Wu, Xi [1 ]
Yang, Aiming [1 ]
Jiang, Qingwei [1 ]
Yao, Fang [1 ]
Feng, Yunlu [1 ]
Guo, Tao [1 ]
Zhou, Weixun [2 ]
Wu, Dongsheng [1 ]
Yan, Xuemin [1 ]
Lai, Yamin [1 ]
Qian, Jiaming [1 ]
Lu, Xinghua [1 ]
Fang, Weigang [3 ]
机构
[1] Beijing Union Med Coll Hosp, Div Gastroenterol, 1 Shuaifuyuan, Beijing 100730, Peoples R China
[2] Beijing Union Med Coll Hosp, Div Pathol, Beijing, Peoples R China
[3] Beijing Union Med Coll Hosp, Div Gen Internal Med, Beijing, Peoples R China
来源
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES | 2018年 / 32卷 / 02期
关键词
Stomach cancer; Prediction model; Risk factor; Endosonography; CONVENTIONAL ENDOSCOPY; DEPTH; DIAGNOSIS;
D O I
10.1007/s00464-017-5754-z
中图分类号
R61 [外科手术学];
学科分类号
摘要
Background Conventional endoscopy and endoscopic ultrasonography (EUS) are used to estimate the invasion depth of early-stage gastric cancers (EGCs), but estimates made by either technique are often inaccurate. We developed a model to determine the invasion depth of EGCs using conventional endoscopy and EUS findings, with pathology results as the reference. Methods We performed a retrospective study of 195 patients (205 lesions) diagnosed with gastric cancers who underwent endoscopy and EUS followed by resection. Based on pathology analyses, lesions (n = 205) were assigned to categories of: mucosa invasion or minute invasion into the submucosal layer less than 500 mu m from the muscularis mucosae (M-SM1) or penetration of 500 mu m or more (>= SM2). The lesions were randomly assigned to derivation (138 lesions) and validation sets (67 lesions). A depth predictive model was proposed in the derivation set using multivariate logistic regression analyses. The discriminative power of this model was assessed in both sets. Results Remarkable redness (OR 5.42; 95% CI 1.32-22.29), abrupt cutting of converging folds (OR 8.58; 95% CI 1.65-44.72), lesions location in the upper third of the stomach (OR 10.26; 95% CI 2.19-48.09), and deep invasion based on EUS findings (OR 16.53; 95% CI 4.48-61.15) significantly associated with >= SM2 invasion. A model that incorporated these 4 variables discriminated between M-SM1 and >= SM2 lesions with the area under the ROC curve of 0.865 in the derivation set and 0.797 in the validation set. In the derivation set, a cut-off score of 8 identified lesions as >= SM2 with 54% sensitivity and 97% specificity. The model correctly predicted the invasion depth 89.86% of lesions; it overestimated the depth of 2.17% of lesions. Conclusions We developed a model to identify EGCs with invasion depth >= SM2 based on endoscopy and EUS findings. This model might reduce overestimation of gastric tumor depth and prevent unnecessary gastrectomy.
引用
收藏
页码:855 / 863
页数:9
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