Risk Factors and Prediction Model for Non-curative Resection of Early Gastric Cancer With Endoscopic Resection and the Evaluation

Abstract

Background and Study Aim: EGC, also known as Early Gastric Cancer is known to lack the lymph node metastasis and confined along the mucosa, which is treated through an endoscopic resection procedure that includes ESD (Endoscopic Submucosal dissection) and EMR (Endoscopic Mucosal Resection). However, some cases underwent residual disease, recurrence, or additional gastrectomy because of non-curative resection. The following research aims to delineate the threat factors causing the non-curative resection as well as develop a predictive model.Patient and Methods: Effort was taken to collect all the records about the health history of pathologically diagnosed EGC who experienced endoscopic treatment in the Department of Endoscopy, the Capital Medical University, and Beijing Friendship Hospital from January 2012 to January 2020. Patients were grouped into two categories primarily; a curative resection group and finally a non-curative resection group based on the outcomes of the postoperative pathological and immunohistochemical examination results. The statistical methods used included single factor analysis, a multivariate logistic regression analysis and a chi-square test. A nomogram for the prediction of non-curative resection was constructed, which included information on age, gender, resection method, postoperative pathology, tumor size, ulcer, treatment, and infiltration depth. Receiver operating characteristic (ROC) curve analysis and calibration were performed to present the predictive accuracy of the nomogram.Results: Of 443 patients with 478 lesions who had undergone ESD or EMR for EGCs, 127 were identified as being treated non-curative resection. Older patients (>60 years), a large tumor size (>30 mm), submucosal lesion, piecemeal resection, EMR for treatment and undifferentiated tumor histology were associated with non-curative resection group. Our risk nomogram showed good discriminated performance in internal validation (bootstrap-corrected area under the receiver-operating characteristic curve, 0.881; P < 0.001).Conclusions: A validated prediction model was developed to identify people who were subject to undergoing a non-curative resection for ESD. The predictive model that we formulated is essential in providing reliable information to guide the decision-making process on the treatment for EGC before undertaking an endoscopic resection.

Endoscopic submucosal dissection for superficial gastrointestinal lesions: European Society of Gastrointestinal Endoscopy (ESGE) Guideline – Update 2022

“…It should be noted that endoscopy alone (even without CE) has almost 80 % accuracy in determining curability by ER, with several prediction models described to decide between ESD or surgery, with good results published in the literature [57][58][59]. Moreover, ESD does not preclude the possibility of subsequent surgery and should be seen as the most definitive T-staging modality.…”

Application of Machine Learning Algorithms to Predict Lymph Node Metastasis in Early Gastric Cancer

“…In summary, we believe Our model contained three important factors: tumour size, tumour grade and depth of tumour invasion. In previous reports, tumour diameter affected lymph node metastasis in early gastric cancer, and the larger was the tumour diameter, the higher was the risk of LNM in patients (31). This phenomenon may be due to larger tumour diameters invading the surrounding tissues more easily.…”

The future of endoscopic resection for early gastric cancer

“…65,73 Some authors have proposed prediction models for noncurative resection of EGC. 74,75 Kim et al 74 analyzed 1639 patients who had undergone ESD for EGCs and 272 were identified as being noncuratively treated with ESD. A large tumor size (≥20 mm), tumor location in the upper body of the stomach, the presence of ulcer, fusion of gastric folds, the absence of mucosal nodularity, spontaneous bleeding, and undifferentiated tumor histology were associated with noncurative resection of ESD.…”

“…Risk scores should be used to estimate the probability of noncurative resection, and this data can be shared with patients to help them make more informed decisions 65,73 . Some authors have proposed prediction models for noncurative resection of EGC 74,75 . Kim et al 74 analyzed 1639 patients who had undergone ESD for EGCs and 272 were identified as being noncuratively treated with ESD.…”