{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T15:32:59Z","timestamp":1792510379872,"version":"4.5.0"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T00:00:00Z","timestamp":1777507200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Immune checkpoint inhibitors (ICIs) have transformed treatment of locally advanced gastric cancer (LAGC), yet response heterogeneity and immune-related adverse events (irAEs) remain major challenges. Systemic inflammation and nutritional status critically modulate antitumor immunity. This study evaluated the dual predictive value of a combined Systemic Immune-Inflammation Index and Prognostic Nutritional Index (SII-PNI) score for therapeutic efficacy and safety in LAGC patients receiving neoadjuvant PD-1\/PD-L1 inhibitor-based therapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We retrospectively analyzed 276 LAGC patients who received PD-1\/PD-L1 inhibitor-based neoadjuvant immunotherapy (January 2019\u2013December 2021). Blood samples were collected within 7 days before treatment initiation. Optimal cut-off values for SII and PNI were determined via ROC analysis to construct the SII-PNI score (Score 0\u20132). Primary endpoints were disease-free survival (DFS), overall survival (OS), tumor response (RECIST 1.1), and irAE incidence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The optimal cut-off values were 736.2 for SII and 48.5 for PNI. Patients with a high SII-PNI score (Score 2) exhibited significantly poorer objective response rates (ORR) compared to the low-risk Score 0 group (22.6% vs. 71.2%, P &amp;lt; 0.001). The SII-PNI score demonstrated superior predictive accuracy for immunotherapy response (AUC\u00a0=\u00a00.750) compared to PD-L1 CPS (AUC\u00a0=\u00a00.711) and Tumor Mutational Burden (TMB, AUC\u00a0=\u00a00.625). Multivariate Cox analysis identified the SII-PNI score as an independent prognostic factor; compared to Score 0, patients with Score 2 faced a more than threefold increased risk of disease recurrence (HR\u00a0=\u00a03.45, 95% CI: 2.40\u20134.95, P &amp;lt; 0.001) and mortality (HR\u00a0=\u00a03.15, 95% CI: 1.85\u20135.36, P &amp;lt; 0.001). Furthermore, the high-risk group (Score 2) had a significantly higher incidence of severe (Grade 3\u20134) irAEs compared to the low-risk group (28.6% vs. 3.6%, P &amp;lt; 0.001).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The SII-PNI score is a robust, non-invasive, and economically accessible biomarker that effectively stratifies outcomes in gastric cancer patients receiving neoadjuvant immunotherapy. It serves as a dual predictor for both poor therapeutic response and increased toxicity, outperforming traditional biomarkers like PD-L1 CPS. This scoring system holds promise for guiding personalized treatment strategies and optimizing patient selection.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1806537","type":"journal-article","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T04:25:45Z","timestamp":1777523145000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["An integrated SII-PNI immune-nutritional scoring system predicts efficacy and immune-related adverse events in locally advanced gastric cancer patients undergoing neoadjuvant immunotherapy"],"prefix":"10.3389","volume":"17","author":[{"given":"Fang","family":"Li","sequence":"first","affiliation":[{"name":"Department of Pathology, The Fourth Hospital of Hebei Medical University","place":["Shijiazhuang, Hebei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Honghai","family":"Guo","sequence":"additional","affiliation":[{"name":"The 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