The implications of dynamic observation of immunoinflammatory indices in patients with resectable gastric cancer: based on latent category trajectory model

Inflammatory immune and tumor markers, identified through laboratory tests, have been shown to predict the prognosis of gastric cancer patients. However, most existing studies have relied on dichotomous classifications or specific cut-off values for their analyses. In this study, we gathered data on NLR, PLR, LMR, SII, PNI, CEA, AFP, CA125, and CA199 from patients before surgery and at 1, 3, 6, 9, and 12 months postoperatively. We then analyzed how the trends of these markers influenced the prognosis of gastric cancer patients using latent category analysis. A total of 93 patients with gastric cancer who underwent radical gastric cancer surgery at the Department of Gastroenterology of Xijing Hospital between January 2017 and December 2018 and met the criteria for natriuresis were selected for inclusion. NLR, PLR, LMR, SII and PNI, as well as CEA, AFP, CA125 and CA199 were calculated and collected from patients preoperatively as well as at 1, 3, 6, 9 and 12 months postoperatively, and the trends of inflammatory markers and tumor markers at multiple time points were plotted in R. Cox regression analyses were performed to find out the independent risk factors that affect the prognosis of patients with gastric cancer. We collected preoperative and postoperative data on inflammatory and tumor markers from 93 gastric cancer patients, analyzing the trends over multiple time points using latent category analysis. Univariate analysis revealed that only the PNI trend (P < 0.013), surgical resection site (P < 0.034), and TNM stage (P < 0.017) were significantly correlated with the prognosis of these patients (P < 0.013). Multifactorial analysis indicated that changes in PNI trends across different groups (P < 0.046) and TNM stage (P < 0.007) were independent risk factors for gastric cancer patients. Evaluation of PNI at multiple time points has implications for the prognosis of patients with gastric cancer.

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Journal
Discover Medicine
Published
2025-02-11
DOI
https://doi.org/10.1007/s44337-025-00230-y
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
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article

The implications of dynamic observation of immunoinflammatory indices in patients with resectable gastric cancer: based on latent category trajectory model

Yajie Guo, Yongtao Du, Xihao Chen, Zhiyu Liu et al.
Discover Medicine
Inflammatory Biomarkers in Disease Prognosis
article

The implications of dynamic observation of immunoinflammatory indices in patients with resectable gastric cancer: based on latent category trajectory model

Yajie Guo, Yongtao Du, Xihao Chen, Zhiyu Liu, Shuai Liu, Jiawei Song, Jipeng Li
article en

Abstract

Inflammatory immune and tumor markers, identified through laboratory tests, have been shown to predict the prognosis of gastric cancer patients. However, most existing studies have relied on dichotomous classifications or specific cut-off values for their analyses. In this study, we gathered data on NLR, PLR, LMR, SII, PNI, CEA, AFP, CA125, and CA199 from patients before surgery and at 1, 3, 6, 9, and 12 months postoperatively. We then analyzed how the trends of these markers influenced the prognosis of gastric cancer patients using latent category analysis. A total of 93 patients with gastric cancer who underwent radical gastric cancer surgery at the Department of Gastroenterology of Xijing Hospital between January 2017 and December 2018 and met the criteria for natriuresis were selected for inclusion. NLR, PLR, LMR, SII and PNI, as well as CEA, AFP, CA125 and CA199 were calculated and collected from patients preoperatively as well as at 1, 3, 6, 9 and 12 months postoperatively, and the trends of inflammatory markers and tumor markers at multiple time points were plotted in R. Cox regression analyses were performed to find out the independent risk factors that affect the prognosis of patients with gastric cancer. We collected preoperative and postoperative data on inflammatory and tumor markers from 93 gastric cancer patients, analyzing the trends over multiple time points using latent category analysis. Univariate analysis revealed that only the PNI trend (P < 0.013), surgical resection site (P < 0.034), and TNM stage (P < 0.017) were significantly correlated with the prognosis of these patients (P < 0.013). Multifactorial analysis indicated that changes in PNI trends across different groups (P < 0.046) and TNM stage (P < 0.007) were independent risk factors for gastric cancer patients. Evaluation of PNI at multiple time points has implications for the prognosis of patients with gastric cancer.

Discover MedicineVol. 2(1)
Xijing Hospital (CN), Air Force Medical University (CN)
Good health and well-being
Openalex Percentile: Top 97%
Inflammatory Biomarkers in Disease Prognosis
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