Li Wenze, Zhao Defeng, Li Wenya
Department of Hematology, The First Affiliated Hospital of China Medical University, No.155 North Nanjing Road, Heping District, Shenyang, China.
Department of Thoracic Surgery, The First Affiliated Hospital of China Medical University, No.155 North Nanjing Road, Heping District, Shenyang, China.
Sci Rep. 2025 Jul 11;15(1):25034. doi: 10.1038/s41598-025-09574-y.
This study investigated the relationship between the Inflammatory Burden Index (IBI) and risks of all-cause and cancer-specific mortality, focusing on its potential to enhance risk stratification. The research included a cohort of 14,835 participants from the American National Health and Nutrition Examination Survey. IBI was calculated using the formula CRP × (neutrophil / lymphocyte). Cox regression analysis was applied to assess the associations. During 223,719.71 person-years of follow-up, 3483 deaths (23.48%) occurred, including 778 (5.24%) from cancer. Mortality rates were 15.57 (all causes) and 3.48 (cancer) per 1,000 person-years. Kaplan-Meier analysis showed the highest IBI quartile had the lowest survival rates for all-cause and cancer-related mortality (Log-Rank p < 0.001). Adjusted models revealed a 23.4% higher risk of all-cause mortality and a 14.1% higher cancer-specific mortality per standard deviation increase in IBI. Smooth curve fitting confirmed a proportional relationship between IBI and mortality risk. ROC curve and reclassification analyses supported IBI's role in improving mortality risk prediction. The findings of this study indicate noteworthy associations between IBI and both all-cause and cancer-specific mortality. Moreover, the results highlight the potential of IBI in enhancing risk stratification for incident all-cause and cancer-specific mortality within the general population.
本研究调查了炎症负担指数（IBI）与全因死亡率和癌症特异性死亡率风险之间的关系，重点关注其增强风险分层的潜力。该研究纳入了来自美国国家健康与营养检查调查的14835名参与者队列。IBI使用公式CRP×（中性粒细胞/淋巴细胞）计算。采用Cox回归分析来评估相关性。在223719.71人年的随访期间，发生了3483例死亡（23.48%），其中778例（5.24%）死于癌症。全因死亡率和癌症死亡率分别为每1000人年15.57例和3.48例。Kaplan-Meier分析显示，IBI最高四分位数组的全因死亡率和癌症相关死亡率生存率最低（对数秩检验p<0.001）。调整后的模型显示，IBI每增加一个标准差，全因死亡率风险升高23.4%，癌症特异性死亡率风险升高14.1%。平滑曲线拟合证实了IBI与死亡风险之间的比例关系。ROC曲线和重新分类分析支持了IBI在改善死亡风险预测方面的作用。本研究结果表明，IBI与全因死亡率和癌症特异性死亡率之间存在显著关联。此外，结果突出了IBI在增强一般人群中全因和癌症特异性死亡率风险分层方面的潜力。
