Lymphocyte-C-reactive protein ratio with calf circumference could better predict survival of patients with non-metastatic cancer

淋巴细胞-C反应蛋白比值与小腿围的比值可以更好地预测非转移性癌症患者的生存率。

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Abstract

Systemic inflammatory responses caused by tumor cells play an important role in the occurrence and development of tumors. The aim of this study was to identify biomarkers that most accurately predict prognoses in patients with non-metastatic cancer and to evaluate their clinical significance when combined with muscle markers. This study retrospectively evaluated 2,797 cancer patients diagnosed with cancer at TNM stages I, II, and III. Lymphocyte-C-reactive protein ratio (LCR) in conjunction with calf circumference (CC) were used (or chosed) after evaluating the predictive value of 13 inflammatory marker combinations and five anthropometric indicators for patient outcomes using the C-index. The Kaplan-Meier method and Cox's proportional hazards regression modeling were used to analyze the individual and combined effects of these two potential biomarkers on overall survival. This study enrolled 1,604 men (57.3%) and 1,193 women (42.7%) with a mean age of 58.75 years. Among the 13 inflammatory nutritional indicators, the LCR was the most accurate predictor of prognoses in patients with non-metastatic cancer. After multifactorial adjustment, we found that low LCR had an adverse effect on overall survival (hazard ratio [HR]: 2.50; 95% confidence interval [CI]: 2.17, 2.88; P < 0.001). Low LCR combined with low CC was also shown to be an independent risk factor for poor overall survival (HR: 2.26; 95% CI: 1.80, 2.83; P < 0.001). Compared with LCR or CC alone, the combination of the two had greater prognostic value for patients with non-metastatic cancer. The LCR can be implemented as a useful biomarker to predict prognoses in patients with non-metastatic cancer. CC is the best anthropometric indicator of muscle loss in patients with non-metastatic cancer. The combination of LCR and CC can better predict the prognosis of patients with non-metastatic cancer, and can provide important information for clinicians to formulate diagnosis and treatment plans.

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