ArticleFrontiers in nutrition2026
Clinical phenotype identification based on inflammation-nutrition-coagulation biomarkers in advanced non-small cell lung cancer.
Article in Frontiers in nutrition, 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
Objective: This study aimed to identify clinically distinct host phenotype subgroups based on inflammation-nutrition-coagulation biomarkers in patients with advanced non-small cell lung cancer (NSCLC). It also evaluated their association with conventional Tumor-Node-Metastasis (TNM) staging. Methods: A total of 1,644 patients with advanced NSCLC were retrospectively included. Twenty-two baseline laboratory indicators spanning inflammation, nutrition, and coagulation were collected. After data cleaning and Z-score standardization, principal component analysis (PCA) was performed for dimensionality reduction. The optimal number of clusters was determined using the elbow method, silhouette coefficient, and Calinski-Harabasz index. Results: The Kaiser-Meyer-Olkin value was 0.631, and Bartlett's test of sphericity was significant ( Conclusion: PCA combined with K-means clustering identified three distinct host phenotype subgroups along the inflammation-nutrition-coagulation axis in advanced NSCLC. These subgroups were independent of TNM staging and provide a new framework for individualized risk stratification and clinical management.
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