Department of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong 261053, China.
Department of Mathematical Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong 261053, China.
J Stroke Cerebrovasc Dis. 2024 Dec;33(12):108076. doi: 10.1016/j.jstrokecerebrovasdis.2024.108076. Epub 2024 Oct 10.
The systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) are novel inflammatory biomarkers used to determine various disease prognoses. However, the effects of these systemic inflammatory markers on all-cause mortality in patients with stroke remain unclear.
We used data from the UK Biobank for this prospective analysis. Overall, 6,020 eligible individuals were included. Over a median follow-up of 13.4 years, 1,233 participants died. We examined the effects of systemic inflammatory markers on all-cause mortality using random survival forest (RSF) and Cox proportional hazards models. Covariate adjustments in the Cox model, selected by RSF, included age, sex, body mass index (BMI), Townsend deprivation index, smoking status, alcohol intake frequency, sleep duration, diabetes, and malignant neoplasms.
In the marginal effect plots and restricted cubic spline analysis for systemic inflammatory markers, LMR exhibited a linear negative correlation, NLR showed a linear positive correlation, and SII and PLR demonstrated a U-shaped association. After covariates were adjusted, the all-cause mortality risk increased by 14 % for LMR <4 (hazards ratio [HR]: 1.14, 95 % confidence interval [CI]: 1.01-1.29; p= 0.03), by 26 % for NLR ≥2 (HR: 1.26; 95 % CI: 1.11-1.43; p < 0.001),by 26 % for PLR ≥175 (HR: 1.26; 95 % CI: 1.07-1.47; p < 0.001), and by 31 % for SII ≥526 (HR: 1.31; 95 % CI, 1.16-1.47; p= 0.014). In addition, sensitivity analyses, excluding participants who had been followed-up for <2 years and those with malignant neoplasms, yielded results consistent with those of previous research.
SII, NLR, PLR, and LMR significantly correlate with all-cause mortality in stroke patients. Thresholds established by the RSF model could potentially refine prognostic decision-making in stroke care.
系统性免疫炎症指数（SII）、中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）和淋巴细胞与单核细胞比值（LMR）是用于确定各种疾病预后的新型炎症生物标志物。然而，这些系统性炎症标志物对中风患者全因死亡率的影响尚不清楚。
我们使用了英国生物库的数据进行这项前瞻性分析。总共纳入了 6020 名符合条件的个体。在中位随访 13.4 年期间，有 1233 名参与者死亡。我们使用随机生存森林（RSF）和 Cox 比例风险模型来检查系统性炎症标志物对全因死亡率的影响。Cox 模型中的协变量调整由 RSF 选择，包括年龄、性别、体重指数（BMI）、汤森剥夺指数、吸烟状况、饮酒频率、睡眠时间、糖尿病和恶性肿瘤。
在系统性炎症标志物的边缘效应图和限制三次样条分析中，LMR 呈线性负相关，NLR 呈线性正相关，SII 和 PLR 呈 U 型关联。调整协变量后，LMR<4 的全因死亡风险增加 14%（风险比[HR]：1.14，95%置信区间[CI]：1.01-1.29；p=0.03），NLR≥2 的全因死亡风险增加 26%（HR：1.26；95%CI：1.11-1.43；p<0.001），PLR≥175 的全因死亡风险增加 26%（HR：1.26；95%CI：1.07-1.47；p<0.001），SII≥526 的全因死亡风险增加 31%（HR：1.31；95%CI：1.16-1.47；p=0.014）。此外，排除随访时间<2 年和患有恶性肿瘤的参与者的敏感性分析结果与之前的研究一致。
SII、NLR、PLR 和 LMR 与中风患者的全因死亡率显著相关。RSF 模型确定的阈值可能有助于改善中风患者的预后决策。
