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Glucose to lymphocyte ratio predicts prognoses in patients with colorectal cancer

Ming Yang, Qi Zhang, Yi‐Zhong Ge, Meng Tang, Xi Zhang, Mengmeng Song, Guo‐Tian Ruan, Xiaowei Zhang, Kangping Zhang, Hanping Shi

2022Asia-Pacific Journal of Clinical Oncology13 citationsDOI

Abstract

BACKGROUND: Colorectal cancer (CRC) is characterized by high morbidity and mortality. Inflammatory, metabolic, and immune factors are closely related to survival of patients with CRC, but their combined impact is unknown. Hence, we chose and evaluated the prognostic value of glucose to lymphocyte ratio (GLR) and a nomogram that include GLR for patients with CRC. METHODS: A total of 1448 patients with CRC were included in our study, and their baseline clinicopathological characteristics and laboratory investigations were collected for analysis. We used Cox proportional hazard regression analyses (both univariate and multivariate) to determine prognostic values of clinical indicators. A nomogram was constructed, and concordance index (C-index) was used to assess the predictive power. RESULTS: Multivariate analyses demonstrated GLR as an independent prognostic factor (hazard ratios 1.060; 95% confidence interval 1.030-1.091; p < .001). A nomogram was constructed integrating factors with clinical significance (sex) and those with independent prognostic value (age, body mass index, tumor stage, and GLR), and the model showed a C-index of .778 (.757-.799), which was higher than that of .738 (.717-.759) for tumor stage. CONCLUSION: GLR can independently predict the prognoses of patients with CRC, and our nomogram provides more accurate prediction than TNM staging.

Topics & Concepts

NomogramMedicineHazard ratioInternal medicineProportional hazards modelOncologyUnivariateConfidence intervalColorectal cancerStage (stratigraphy)Multivariate analysisMultivariate statisticsBody mass indexUnivariate analysisConcordanceCancerStatisticsBiologyMathematicsPaleontologyInflammatory Biomarkers in Disease PrognosisCancer Immunotherapy and BiomarkersCancer, Lipids, and Metabolism