ArticleCancer informatics2026
The Association of Neutrophil-To-Lymphocyte and Platelet-To-Lymphocyte Ratios With Distant Metastasis in Vietnamese Gastric Cancer Patients.
Article in Cancer informatics, 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
Background: Gastric cancer (GC) remains a leading cause of mortality in Vietnam, where distant metastasis is frequently present at diagnosis. Since accessible biomarkers are scarce, we evaluated the association of Neutrophil-to-Lymphocyte Ratio (NLR) and Platelet-to-Lymphocyte Ratio (PLR) with distant metastasis in a Vietnamese cohort to develop a model for patient stratification. Methods: This retrospective study analyzed 114 patients, categorizing into metastatic (Stage IV) and non-metastatic groups per AJCC 8 Results: Distant metastasis was 44.7% of cases. Optimal cutoffs of 2.0 for NLR and 181.5 for PLR were identified. Both markers were significantly higher in metastatic group and positively correlated with disease progression. LASSO identified PLR, NLR, and tumor location as the most robust determinants. In multivariable analysis, only multiple tumor location and high PLR remained independent prognostic factors. The combined model integrating clinical factors with NLR and PLR significantly outperformed clinical features alone (AUC: 0.766 vs. 0.619, p=0.0036), with an optimism-corrected C-index of 0.708. At a 0.586 threshold, the model achieved 82.5% specificity and 62.7% sensitivity, supporting a conservative "rule-out" strategy. Calibration slope was 0.659. DCA demonstrated superior net benefit across a 15%-90% risk range; specifically, at a 40% threshold, model spared 19 per 100 patients from unnecessary intervention. Conclusion: This study establishes the first baseline for NLR and PLR in the Vietnamese cohort, showing an association of these biomarkers with GC distant metastasis. A model integrating PLR, NLR and tumor location optimizes patient stratification and resource allocation in resource-constrained healthcare environments.
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