Cheng Quankai, Liu Chang, Zhong Haicheng, Wang Ziming, Zhou Sheng, Sun Jingjing, Zhao Sihai, Deng Jie
Department of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
PLoS One. 2025 Jun 24;20(6):e0325949. doi: 10.1371/journal.pone.0325949. eCollection 2025.
Several novel biomarkers, including the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), aggregate index of systemic inflammation (AISI), platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and monocyte-lymphocyte ratio (MLR), are linked to the systemic immunity inflammation response and the odds and severity of abdominal aortic calcification (AAC). However, still no previous research has systematically compared their association with severe AAC.
This study utilized a cross-sectional approach, examining a cohort of 3,047 adults from National Health and Nutrition Examination Survey (NHANES). Weighted logistic regression was utilized to investigate the associations between a range of immunoinflammatory biomarkers and the likelihood of severe AAC. Segmented regression and limited cubic spline models were used in the investigation to characterize the threshold effects and non-linear correlations. Additionally, subgroup and interaction tests, Spearman correlation, least absolute shrinkage, and selection operator regression studies were conducted.
The 3047 participants included in this study had a mean age of 58.63 years and 51.79% were female. After fully adjusting for all covariates, the ln-SIRI (OR 1.39 [CI 1.10-1.74], P = 0.005), ln-AISI (OR 1.26 [1.03-1.53], P = 0.024), and ln-MLR (OR 1.62 [1.15-2.30], P = 0.006) were significantly correlated with the odds of severe AAC. A non-linear dose-response relationship was observed between ln-SII and severe AAC. Additional subgroup analyses revealed that this relationship was more evident in the diabetic population. Additionally, MLR (AUC = 0.644) predicted the prevalence of severe AAC better than other biomarkers, and the prediction model constructed in conjunction with screened clinical indicators showed good predictive value (AUC = 0.853).
In this study, we comprehensively evaluated and compared the associations between six biomarkers and severe AAC, and developed a clinical prediction model using the MLR with the best predictive effect. However, cohort studies and model validation are still needed in the future to further confirm their relationship.
包括全身免疫炎症指数（SII）、全身炎症反应指数（SIRI）、全身炎症聚集指数（AISI）、血小板淋巴细胞比值（PLR）、中性粒细胞淋巴细胞比值（NLR）和单核细胞淋巴细胞比值（MLR）在内的几种新型生物标志物与全身免疫炎症反应以及腹主动脉钙化（AAC）的几率和严重程度相关。然而，此前尚无研究系统地比较它们与重度AAC的关联。
本研究采用横断面研究方法，对来自美国国家健康与营养检查调查（NHANES）的3047名成年人队列进行了检查。采用加权逻辑回归来研究一系列免疫炎症生物标志物与重度AAC可能性之间的关联。在调查中使用分段回归和受限立方样条模型来描述阈值效应和非线性相关性。此外，还进行了亚组和交互作用检验、Spearman相关性分析、最小绝对收缩和选择算子回归研究。
本研究纳入的3047名参与者的平均年龄为58.63岁，51.79%为女性。在对所有协变量进行充分调整后，ln-SIRI（比值比[OR]1.39[可信区间{CI}1.10 - 1.74]，P = 0.005）、ln-AISI（OR 1.26[1.03 - 1.53]，P = 0.024）和ln-MLR（OR 1.62[1.15 - 2.30]，P = 0.006）与重度AAC的几率显著相关。ln-SII与重度AAC之间观察到非线性剂量反应关系。进一步的亚组分析显示，这种关系在糖尿病患者群体中更为明显。此外，MLR（曲线下面积[AUC]=0.644）对重度AAC患病率的预测优于其他生物标志物，结合筛选出的临床指标构建的预测模型显示出良好的预测价值（AUC = 0.853）。
在本研究中，我们全面评估并比较了六种生物标志物与重度AAC之间的关联，并利用预测效果最佳的MLR建立了临床预测模型。然而，未来仍需要进行队列研究和模型验证以进一步证实它们之间的关系。
