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. 2026 Aug 12;17:1907116. doi: 10.3389/fimmu.2026.1907116

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Copyright © 2026 Li, Mu, Guo, Zheng, Yang, Wang, Shi, Xu, Tian, Ma and Zhao.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Flowchart outlining a study of 738 patients with locally advanced gastric or EGJ adenocarcinoma treated with neoadjuvant PD-1 inhibitor and chemotherapy, divided into training, internal validation, and external validation cohorts. A pretreatment peripheral blood panel assesses endocrine, nutrition, and inflammation markers, followed by machine learning model comparison using a five-marker ENI panel, leading to ENI-Score calculation and benefit stratification. — Study design and ENI-score workflow, from multicenter cohort allocation through pretreatment marker collection, machine-learning model comparison, and tertile-based clinical stratification.