Li Huimin, Huang Jingda, Sun Mindan
Department of Nephrology, The First Hospital of Jilin University, Changchun, China.
Ren Fail. 2025 Dec;47(1):2553808. doi: 10.1080/0886022X.2025.2553808. Epub 2025 Sep 7.
Inflammation and hyperuricemia are closely associated with chronic kidney disease (CKD). The systemic inflammation response index (SIRI), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are emerging as novel biomarkers. While, the synergistic effects of these biomarkers with hyperuricemia on CKD remain unclear.
We analyzed 10,226 participants from 2015-2020 National Health and Nutrition Examination Survey (NHANES). The relationships among inflammatory biomarkers (SIRI, SII, MLR, NLR, and PLR), hyperuricemia and CKD were assessed by multivariate logistic regression models. Restricted cubic splines (RCS) and segmented regression models were used to evaluate the nonlinear relationships. The diagnostic performance was evaluated using receiver operating characteristic (ROC) curve, and incremental predictive value was further calculated by Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI). The interaction analysis was performed to explore the combined effects.
SIRI, SII, MLR, and NLR were significantly linked with CKD. MLR exhibited a threshold effect at 0.22 (-non-linear < 0.05), with significantly stronger association with CKD above this cutoff. SIRI demonstrated the best diagnostic accuracy among these biomarkers. Significant interactions were observed between hyperuricemia and inflammatory biomarkers (SIRI, SII, MLR, NLR), indicating that the association between inflammatory biomarkers and CKD is more pronounced in the presence of hyperuricemia.
There were significant associations between inflammatory biomarkers (SII, SIRI, NLR, MLR) and CKD, with particularly stronger correlations observed in patients with hyperuricemia.
炎症和高尿酸血症与慢性肾脏病(CKD)密切相关。全身炎症反应指数(SIRI)、全身免疫炎症指数(SII)、单核细胞与淋巴细胞比值(MLR)、中性粒细胞与淋巴细胞比值(NLR)以及血小板与淋巴细胞比值(PLR)正成为新的生物标志物。然而,这些生物标志物与高尿酸血症对CKD的协同作用仍不清楚。
我们分析了2015 - 2020年美国国家健康与营养检查调查(NHANES)中的10226名参与者。通过多变量逻辑回归模型评估炎症生物标志物(SIRI、SII、MLR、NLR和PLR)、高尿酸血症与CKD之间的关系。使用受限立方样条(RCS)和分段回归模型评估非线性关系。使用受试者工作特征(ROC)曲线评估诊断性能,并通过净重新分类改善(NRI)和综合判别改善(IDI)进一步计算增量预测值。进行交互分析以探索联合效应。
SIRI、SII、MLR和NLR与CKD显著相关。MLR在0.22处表现出阈值效应(-非线性<0.05),高于此临界值时与CKD的关联显著更强。SIRI在这些生物标志物中表现出最佳的诊断准确性。在高尿酸血症与炎症生物标志物(SIRI、SII、MLR、NLR)之间观察到显著的相互作用,表明在存在高尿酸血症的情况下,炎症生物标志物与CKD之间的关联更为明显。
炎症生物标志物(SII、SIRI、NLR、MLR)与CKD之间存在显著关联,在高尿酸血症患者中观察到的相关性尤其更强。