中国实用外科杂志 ›› 2025, Vol. 45 ›› Issue (07): 794-800.DOI: 10.19538/j.cjps.issn1005-2208.2025.07.13

• 论著 • 上一篇    下一篇

局部进展期胃癌新辅助化疗联合免疫治疗主要病理缓解临床预测模型构建研究

段开鹏,李东宝,王鹏博,李炜康,孙小童,顾力行,王运良,周    进   

  1. 苏州大学附属第一医院胃外科,江苏苏州 215006 
  • 出版日期:2025-07-01 发布日期:2025-07-27

  • Online:2025-07-01 Published:2025-07-27

摘要: 目的    分析局部进展期胃癌病人行新辅助化疗联合免疫治疗获得主要病理缓解(MPR)的影响因素并建立预测模型。方法    前瞻性收集2022年1月至2025年5月苏州大学附属第一医院胃外科收治的48例行新辅助化疗联合免疫治疗的局部进展期胃癌病人临床资料。根据术后病理学肿瘤退缩分级评估新辅助化疗联合免疫治疗的效果,分为MPR组(23例)和非MPR组(25例)。对比两组病人新辅助前后各项指标,分析MPR的预测因素,并构建列线图和贝叶斯回归模型。结果    MPR组与非MPR组病人在cN分期、印戒细胞癌占比、Lauren分型、联合阳性评分(CPS)、ypT分期及ypN分期方面差异有统计学意义(P<0.05)。多因素回归分析结果显示,cN分期早(OR=0.753,95%CI 0.430-0.872,P=0.025)、非印戒细胞癌(OR=1.873,95%CI 1.451-2.314,P=0.043)及CPS≥5分(OR=2.241,95%CI 1.692-2.868,P=0.023)是预测MPR的独立保护因素。基于上述3个因素构建的列线图模型,C指数为0.781(95%CI 0.613-0.927)。贝叶斯回归模型结果显示其预测MPR的受试者工作特征曲线(ROC)下面积为0.736 (95%CI 0.579-0.883)。结论    基于cN分期、是否为印戒细胞癌以及CPS评分构建的列线图和贝叶斯回归模型能够有效筛选胃癌新辅助免疫治疗敏感人群,有较高的临床应用价值。

关键词: 局部进展期胃癌, 新辅助化疗, 免疫治疗, 主要病理缓解, 影响因素

Abstract: To analyze the influencing factors of major pathological response (MPR) in patients with locally advanced gastric cancer undergoing neoadjuvant immunotherapy combined with chemotherapy and to establish a predictive model. Methods    The clinical data of 48 patients with locally advanced gastric cancer undergoing neoadjuvant immunotherapy combined with chemotherapy admitted to the Department of Gastric Surgery of the First Affiliated Hospital of Soochow University between January 2022 and May 2025 were prospectively collected. The effect of neoadjuvant immunotherapy combined with chemotherapy was evaluated based on the tumor regression grade in postoperative pathology, and the patients were divided into the MPR group (23 cases) and the non-MPR group (25 cases).The parameters before and after neoadjuvant therapy were compared between the two groups. The predictive factors of MPR were analyzed, and a nomogram and Bayesian regression model were constructed. Results  There were significant statistical differences between the MPR group and the non-MPR group in cN stage, the proportion of signet ring cell carcinoma, Lauren classification, CPS  score, ypT stage and ypN stage (P<0.05). Multivariate regression analysis showed early cN stage (OR=0.753, 95%CI 0.430-0.872, P=0.025), non-signet ring cell carcinoma (OR=1.873, 95%CI 1.451-2.314, P=0.043), and CPS≥5 points (OR=2.241, 95%CI 1.692-2.868, P=0.023) was an independent protective factor for predicting MPR. The nomogram model constructed based on the above three factors had a C-index of 0.781 (95%CI 0.613-0.927). The Bayesian regression model showed the area under the ROC curve for predicting MPR was 0.736 (95%CI 0.579-0.883). Conclusion    The nomogram and Bayesian regression model based on cN staging, whether it is signet ring cell carcinoma and CPS score can effectively screen the sensitive population of neoadjuvant immunotherapy for gastric cancer with high clinical application value.

Key words: locally advanced gastric cancer, neoadjuvant chemotherapy, chimmunotherapy, major pathological response, influencing factors