Development and validation of nomogram for predicting pathological complete response to neoadjuvant chemotherapy and immunotherapy for locally advanced gastric cancer: a multicenter real-world study in China

作者：Hao Cui, Rui Li, Liqiang Song, Yongpu Yang, Zhen Yuan, Xin Zhou, Junfeng Du, Chaojun Zhang, Hong Xu, Lin Chen, Yan Shi, Jianxin Cui, Bo Wei · 发表于：Frontiers in Immunology · 年份：2025 · DOI：10.3389/fimmu.2025.1603196 · 被引用次数：3 · 研究领域：Gastric Cancer Management and Outcomes、Inflammatory Biomarkers in Disease Prognosis、Esophageal Cancer Research and Treatment

Background: The combination of neoadjuvant chemotherapy and immunotherapy (NICT) brings a higher proportion of pathological complete response (pCR) compared with neoadjuvant chemotherapy for locally advanced gastric cancer (LAGC). Here we constructed and validated a prediction model to provide a clinical reference for predicting pCR. Methods: 456 patients who accepted radical gastrectomy after NICT in seven large-scale gastrointestinal medical centers from Jan 2020 to Jan 2025 were enrolled in this study, with 320 patients in the training set and 136 patients in the validation set. The uni- and multivariate logistic regression model were used to evaluate the factors influencing pCR and a nomogram model was constructed. The area under the receiver operating characteristic curve (AUC), the calibration curve and decision curve analysis (DCA) were used to evaluate the discrimination, accuracy and clinical value of the nomogram model. Results: There was no significant difference in the baseline characteristics between training and validation set. The pCR and MPR rates were respectively 16.2% and 39.5%. Complete response by abdominal enhanced CT, less diameter of tumor bed, non-signet-ring cell, ages≥70 years old, and CEA<4.25 ng/mL were proved as the independent predictors for pCR (P<0.05). The nomogram model showed that the AUC (95%CI) predicting the pCR were 0.862 (95% CI: 0.807-0.916) in the training set and 0.934(95%CI: 0.889-0.979) in the validation set. The calibration curve...