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Updated: Aug 4, 2025

Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024
Lymphocyte subset is more suitable than systemic inflammatory response biomarker and immunoglobulin in constructing
Tianyi Fang1, Xin Yin1, Yufei Wang1
1Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Abstract:
The serum factors of inflammation are known to be useful prognostic indicators of gastric cancer (GC). However, few studies have made comparisons to screen out more suitable biomarkers for the construction of Nomogram models. In this study, 566 patients who underwent radical gastrectomy were randomly selected. We evaluated the prognostic value of markers of systemic inflammation, including WBC, NLR, PLR, circulating total T cells, CD4+T cells, CD8+T cells and CD19+B cells, serum IgA, IgM, IgE and IgG, and compared them with traditional tumor markers (CEA, CA19-9, CA72-4 and CA125). Kaplan‒Meier analysis was used to analyze the correlation between biomarkers and overall survival (OS). We used time-dependent ROC analysis to investigate the prognostic accuracy of each biomarker. The risk of death was evaluated by the Cox regression model, and the Nomogram model was constructed by R software. We found that circulating total T cells, CD8+T cells, CEA, and CA125 had statistical significance in predicting advanced GC prognosis. Circulating CD8+T cells and CA125 were continuously superior to circulating total T cells and CEA in the prediction of 5-year OS. Cox regression found that CA125, circulating CD8+T cells, sex, and lymph node metastasis rate were independent risk factors for advanced GC. Furthermore, we combined all these predictors to construct a nomogram, which can supplement the AJCC 8th system. According to the comparison with commonly used serum immune biomarkers, circulating CD8+T cells is more sensitive to advanced GC. The prediction function of the Nomogram will supplement the traditional AJCC system, which contributes to individual survival prediction.

