ArticleAmerican journal of translational research2026
Correlation of immune-inflammatory and tumor markers with lymph node metastasis in gastric cancer.
Article in American journal of translational research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveTo evaluate the combined predictive value of immune-inflammatory and tumor markers for lymph node metastasis (LNM) in gastric cancer (GC) patients.
methodsWe conducted a retrospective study of 207 GC patients who underwent radical gastrectomy. Based on postoperative histology, patients were categorized into LNM and non-LNM groups. Preoperative serologic levels of markers including carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA199), carbohydrate antigen 72-4 (CA724), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), Lymphocyte-to-Monocyte Ratio (LMR), Interleukin-6 (IL-6), and C-Reactive Protein (CRP) were collected. A nomogram prediction model was developed using multivariate logistic regression. Internal validation was performed using Bootstrap resampling, and external validation was conducted on an independent cohort of 97 patients.
resultsLNM was present in 55 (26.6%) patients in the training cohort. Multivariate analysis identified preoperative levels of CEA (odds ratio [OR]=1.52, P<0.001), CA724 (OR=1.24, P<0.001), NLR (OR=2.86, P<0.001), and IL-6 (OR=1.97, P<0.001) as independent risk factors for LNM. The nomogram model incorporating these four factors demonstrated excellent discrimination, with an area under the curve (AUC) of 0.93. The model significantly outperformed conventional clinicopathologic indicators (P<0.001). Good calibration and clinical utility were confirmed by calibration curves and decision curve analysis, respectively. The model maintained strong predictive performance in both internal (AUC=0.92) and external (AUC=0.91) validation cohorts.
conclusionThe combination of CEA, CA724, NLR, and IL-6 serves as an effective preoperative predictor of LNM in GC. The nomogram model based on these markers provides a reliable, non-invasive tool for individualized risk assessment and treatment planning.
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