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Inflammatory Burden As a Prognostic Biomarker for Cancer

Overview
Journal Clin Nutr
Publisher Elsevier
Date 2022 May 3
PMID 35504166
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Abstract

Background And Aims: Systemic inflammation is the most representative host-tumor interaction in cancer. This study aimed to develop a novel inflammatory burden index (IBI) to assess the inflammatory burden of different cancers and predict the prognosis of patients with cancer.

Methods: A total of 6359 cancer patients admitted to multiple centers from 2012 through 2019 were included in this study. The IBI was formulated as C-reaction protein × neutrophil/lymphocyte. Survival differences between the groups were compared using the Kaplan-Meier method. Cox proportional hazard regression analysis was used to estimate the hazard ratio (HR) and 95% confidence interval (CI). Logistic regression analysis was used to assess the association between the inflammatory burden index and outcomes.

Results: Cancers assessed by the IBI could be classified as high, moderate, or low inflammatory burden and had different prognostic stratification effects (46.5% vs 61.0% vs 83.0%; P < .001). Compared with other systemic inflammation biomarkers, the IBI had the highest accuracy in predicting survival. Patients with a high IBI had significantly lower survival rates than those with a low IBI (45.7% vs 69.1%; P < .001). For every standard deviation increase in the IBI, the risk of poor prognosis for patients with cancer increased by 10.3% (HR, 1.103; 95% CI, 1.072-1.136; P < .001). The IBI could be used as a useful prognostic supplement in the pathological stage. A high IBI was an independent high-risk factor that affected patient's physical condition, malnutrition, cachexia, and short-term outcomes and an independent risk factor for patients with cancer in both validation cohorts a (hazard ratio, 1.114; 95% confidence interval, 1.072-1.157; P < .001) and b (hazard ratio, 1.125; 95% confidence interval, 1.060-1.193; P < .001).

Conclusions: The IBI, as a novel indicator of systemic inflammation, is a feasible and promising predictive biomarker in patients with cancer and can be used to assess the inflammatory burden of different cancers.

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