Prediction Model of Tumor Regression Grade for Advanced Gastric Cancer After Preoperative Chemotherapy

Abstract

Background: Preoperative chemotherapy (PCT) has been considered an important treatment for advanced gastric cancer (AGC). The tumor regression grade (TRG) system is an effective tool for the assessment of patient responses to PCT. Pathological complete response (TRG = 0) of the primary tumor is an excellent predictor of better prognosis. However, which patients could achieve pathological complete response (TRG = 0) after chemotherapy is still unknown. The study aimed to find predictors of TRG = 0 in AGC. Methods: A total of 304 patients with advanced gastric cancer from July 2009 to November 2018 were enrolled retrospectively. All patients were randomly assigned (2:1) to training and internal validation groups. In addition, 124 AGC patients receiving PCT from December 2018 to June 2020 were included prospectively in the external validation cohort. A prediction model for TRG = 0 was established based on four predictors in the training group and was validated in the internal and external validation groups. Results: Through univariate and multivariate analyses, we found that CA199, CA724, tumor differentiation and short axis of the largest regional lymph node (LNmax) were independent predictors of TRG = 0. Based on the four predictors, we established a prediction model for TRG = 0. The AUC values of the prediction model in the training, internal and external validation groups were 0.84, 0.73 and 0.82, respectively. Conclusions: We found that CA199, CA724, tumor differentiation and LNmax were associated with pathological response in advanced gastric cancer. The prediction model could provide guidance for clinical work.