A discrimination model by machine learning to avoid gastrectomy for early gastric cancer.

Aim: Gastrectomy is recommended for patients with early gastric cancer (EGC) because the possibility of lymph node metastasis (LNM) cannot be completely denied. The aim of this study was to develop a discrimination model to select patients who do not require surgery using machine learning. Methods: Data from 382 patients who received gastrectomy for gastric cancer and who were diagnosed with pT1b were extracted for developing a discrimination model. For the validation of this discrimination model, data from 140 consecutive patients who underwent endoscopic resection followed by gastrectomy, with a diagnosis of pT1b EGC, were extracted. We applied XGBoost to develop a discrimination model for clinical and pathological variables. The performance of the discrimination model was evaluated based on the number of cases classified as true negatives for LNM, with no false negatives for LNM allowed. Results: Lymph node metastasis was observed in 95 patients (25%) in the development cohort and 11 patients (8%) in the validation cohort. The discrimination model was developed to identify 27 (7%) patients with no indications for additional surgery due to the prediction of an LNM-negative status with no false negatives. In the validation cohort, 13 (9%) patients were identified as having no indications for additional surgery and no patients with LNM were classified into this group. Conclusion: The discrimination model using XGBoost algorithms could select patients with no risk of LNM from patients with pT1b EGC. This discrimination model was considered promising for clinical decision-making in relation to patients with EGC.

[A case of intragastric wall abscess formation during bevacizumab combined chemotherapy].

A 38-year-old man was given a diagnosis of as sigmoid colon cancer and underwent sigmoid colectomy. Post-operative pathological staging was stage IIIb. He then underwent adjuvant chemotherapy. One year and 4 months after the surgery, CT scans revealed multiple liver and lung metastases. He was given mFOLFOX6+bevacizumab, which was changed later to FOLFIRI+bevacizumab. After these chemotherapies, he was admitted to the hospital due to sudden abdominal pain and high grade fever. Obstructive jaundice was initially diagnosed, but detailed study of initial CT revealed intragastric wall abscess. After the drainage of the abscess, his conditions improved. We speculated that the abscess formation was caused by mucosal damage due to bevacizumab.