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Original Research

Prognostic Implication of Metabolic Syndrome in Patients with Nasopharyngeal Carcinoma: A Large Institution-Based Cohort Study from an Endemic Area

, , , , , , ORCID Icon & ORCID Icon show all
Pages 9355-9366 | Published online: 24 Dec 2021

Figures & data

Table 1 Baseline Characteristics of 2003 Patients with Nasopharyngeal Carcinoma

Table 2 Baseline Characteristics of Nasopharyngeal Carcinoma Patients with or without Metabolic Syndrome

Figure 1 Kaplan–Meier curve analysis of survival probabilities of NPC patients stratified by metabolic syndrome. (A) Progression-free survival. (B) Cancer specific survival. (C) Overall survival.

Abbreviation: MetS, metabolic syndrome.
Figure 1 Kaplan–Meier curve analysis of survival probabilities of NPC patients stratified by metabolic syndrome. (A) Progression-free survival. (B) Cancer specific survival. (C) Overall survival.

Table 3 Univariate Analysis of Prognostic Factors in Patients with Nasopharyngeal Carcinoma

Table 4 Multivariable Analysis of Prognostic Factors in Patients with Nasopharyngeal Carcinoma

Figure 2 Metabolic profile analysis of NPC patients with and without metabolic syndrome. (A) Partial least-squares discrimination analysis (PLS-DA) of the serum metabolomic file of NPC patients in the MetS and NMetS groups (n = 5). Each symbol represents the data of an individual patient. (B) Fold change analysis discovering differential serum metabolites, which were identified with a log2 (FC) of MetS/NMetS > 1 or < −1. (C) Heatmap showing the top 50 differential serum metabolites. Differential serum metabolites were identified with p<0.05 using Student’s t-test.

Abbreviations: MetS, metabolic syndrome; NMetS, non-metabolic syndrome.
Figure 2 Metabolic profile analysis of NPC patients with and without metabolic syndrome. (A) Partial least-squares discrimination analysis (PLS-DA) of the serum metabolomic file of NPC patients in the MetS and NMetS groups (n = 5). Each symbol represents the data of an individual patient. (B) Fold change analysis discovering differential serum metabolites, which were identified with a log2 (FC) of MetS/NMetS > 1 or < −1. (C) Heatmap showing the top 50 differential serum metabolites. Differential serum metabolites were identified with p<0.05 using Student’s t-test.

Figure 3 Enrichment and pathway analysis of differential metabolites. (A) Bar plot of KEGG pathway analysis of differential metabolites; (B) dot plot of KEGG pathway analysis of differential metabolites.

Figure 3 Enrichment and pathway analysis of differential metabolites. (A) Bar plot of KEGG pathway analysis of differential metabolites; (B) dot plot of KEGG pathway analysis of differential metabolites.