Model to identify early-stage gastric cancers with deep invasion of submucosa based on endoscopy and endoscopic ultrasonography findings.
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.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Gástricas
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Modelos Estatísticos
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Gastroscopia
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Endossonografia
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Mucosa Gástrica
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Invasividade Neoplásica
Tipo de estudo:
Diagnostic_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
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Screening_studies
Limite:
Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article