CA724 Predicts Tumor Regression Grade in Locally Advanced Gastric Cancer Patients with Neoadjuvant Chemotherapy.

Abstract

Purpose: Tumor regression grade (TRG) is widely used to evaluate the efficacy of neoadjuvant chemotherapy (NCT) and it is related to many clinicopathological factors. However, whether TRG can be predicted by clinical characteristics is unknown. Methods: 141 locally advanced gastric cancer (GC) patients who underwent NCT and curative operation were retrospectively analyzed. TRG is reevaluated according to the CAP guideline. The values of CA199, CA125 and CA724 before NCT (pre-) and after NCT (post-) were extracted from our database. Survival curves on overall survival (OS) were obtained by Kaplan-Meier method, and differences were analyzed by log-rank test. Associations between categorical variables were explored by chi-square test or Fisher's exact method. Univariable and multivariate analyses were performed by logistic regression model or Cox proportional hazard regression model. Results: TRG was related to OS (P < 0.001), especially when divided into responders (TRG 0-1) and non-responders (TRG 2-3). Pre-CA724 (p = 0.029) and post-CA199 (p = 0.038) were related to OS. In multivariable analysis, pre-CA724 (p = 0.015) and post-CA199 (p = 0.007) were independent prognostic factors for OS, respectively. The changes (diff-) of all tumor markers were not related to OS. Among the clinical characteristics, pre-CA724 (P = 0.047) and tumor size (P = 0.012) were related to TRG, while pre-CA199 (P = 0.377) and pre-CA125 (P = 0.856) were not. In logistics analysis, pre-CA724 (P = 0.032), tumor size (P = 0.011) and tumor location (P = 0.047) were independent risk factors to pathological response. Conclusion: CA724 was an independent prognostic factor for OS and could be used to predict pathological response.

• Authors: Yilin Tong, Yanmei Zhu, Yan Zhao, Chengyao Jiang, Wentao Wang, Zexing Shan, Fan Sun, Dong Liu, Jianjun Zhang
• Journal: Journal of Cancer (J Cancer) Vol. 12 Issue 21 Pg. 6465-6472 ( 2021) ISSN: 1837-9664 [Print] Australia
• PMID: 34659537 (Publication Type: Journal Article)
• Copyright: © The author(s).