Your browser doesn't support javascript.
loading
Model to identify early-stage gastric cancers with deep invasion of submucosa based on endoscopy and endoscopic ultrasonography findings.
Cheng, Jieyao; Wu, Xi; Yang, Aiming; Jiang, Qingwei; Yao, Fang; Feng, Yunlu; Guo, Tao; Zhou, Weixun; Wu, Dongsheng; Yan, Xuemin; Lai, Yamin; Qian, Jiaming; Lu, Xinghua; Fang, Weigang.
Afiliação
  • Cheng J; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Wu X; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China. wxpumch@163.com.
  • Yang A; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China. yangaiming@medmail.com.cn.
  • Jiang Q; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Yao F; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Feng Y; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Guo T; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Zhou W; Division of Pathology, Peking Union Medical College Hospital, Beijing, China.
  • Wu D; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Yan X; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Lai Y; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Qian J; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Lu X; Division of Gastroenterology, Peking Union Medical College Hospital, 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
  • Fang W; Division of General Internal Medicine, Peking Union Medical College Hospital, Beijing, China.
Surg Endosc ; 32(2): 855-863, 2018 02.
Article em En | MEDLINE | ID: mdl-28733747
ABSTRACT

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 µm from the muscularis mucosae (M-SM1) or penetration of 500 µm 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.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Gástricas / Modelos Estatísticos / Gastroscopia / Endossonografia / Mucosa Gástrica / Invasividade Neoplásica Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Gástricas / Modelos Estatísticos / Gastroscopia / Endossonografia / Mucosa Gástrica / Invasividade Neoplásica Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2018 Tipo de documento: Article