Analysis of the influencing factors of pathological response to neoadjuvant chemotherapy in locally advanced gastric cancer

Ma Deyuan; Wang Rui; Zhang Fengzhu; Han Jing; Zeng Miaomiao; Guan Quanlin

doi:10.3760/j.issn.1673-4777.2025.05.013

Abstract：Objective To investigate the influencing factors of pathological response in patients with locally advanced gastric cancer(LAGC)receiving neoadjuvant chemotherapy(NACT).Methods The clinical data of 216 LAGC patients who underwent NACT combined with radical gastrectomy in the First Hospital of Lanzhou University from January 2014 to December 2020 were collected and retrospectively analyzed.According to tumor regression grade(TRG),the patients were divided into good pathological response group(TRG 0/1,38 cases)and poor pathological response group(TRG 2/3,178 cases).Logistic regression analysis was used to evaluate the influencing factors,and receiver operating characteristic(ROC)curve was used to analyze the predictive efficacy of independent influencing factors.Results Compared with the poor pathological response group,the good patho-logical response group was characterized by good histological differentiation(P=0.014),higher proportion Borrmann type Ⅱ(P=0.003),earlier T stage(P=0.003),more △ number of positive tumor markers(P=0.005)and lower Ki-67(P＜0.001).Logistic regression analysis showed that high histological differentiation(P=0.007),early T stage(P=0.034),more △ number of positive tumor markers(P=0.002)and low Ki-67(P＜0.001)were independent factors for good pathological response.ROC curve analysis showed that the area under the curve of the above indicators to predict good pathological response was 0.875(95％confidence interval:0.805-0.945)(P＜0.001).Conclusions The good histological differentiation,Borrmann type Ⅱ,early T stage,more △ number of tumor markers and low Ki-67 were the influencing factors of good pathological response in LAGC patients after NACT.The good histological differentiation,early T stage,more △ number of tumor markers and low Ki-67 were independent influencing factors.The combination of each index had good predictive value.