Rocky Mountain Regional VAMC, and University of Colorado School of Medicine, Denver, Colorado.
Portland VAMC and Oregon Health Sciences University, Portland.
Arthritis Rheumatol. 2023 Feb;75(2):232-241. doi: 10.1002/art.42333. Epub 2022 Dec 23.
This study was conducted to assess the utility of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in predicting radiographic sacroiliitis and active disease in axial spondyloarthritis (SpA) and to explore the association between use of a tumor necrosis factor inhibitor (TNFi) and these laboratory values compared with traditional inflammatory markers.
Observational data from the Program to Understand the Longterm Outcomes in Spondyloarthritis (PULSAR) registry were analyzed. We generated receiver operating characteristic curves to calculate laboratory cutoff values; we used these values in multivariable logistic regression models to identify associations with radiographically confirmed sacroiliitis and active disease. We also used logistic regression to determine the likelihood of elevated laboratory values after initiation of TNFi.
Most study participants (n = 354) were White, male, and HLA-B27 positive. NLR (odds ratio [OR] 1.459, P = 0.034), PLR (OR 4.842, P < 0.001), erythrocyte sedimentation rate (OR 4.397, P < 0.001), and C-reactive protein (CRP) level (OR 2.911, P = 0.001) were independent predictors of radiographic sacroiliitis. Models that included PLR with traditional biomarkers performed better than those with traditional biomarkers alone. NLR (OR 6.931, P = 0.002) and CRP (OR 2.678, P = 0.004) were predictors of active disease, but the model that included both NLR and CRP performed better than CRP alone. TNFi use reduced the odds of elevated NLR (OR 0.172, P < 0.001), PLR (OR 0.073, P < 0.001), erythrocyte sedimentation rate (OR 0.319, P < 0.001), and CRP (OR 0.407, P < 0.001), but models that included NLR or PLR and traditional biomarkers performed best.
These findings demonstrate an association between NLR and PLR and sacroiliitis and disease activity, with NLR and PLR showing response after TNFi treatment and adding useful clinical information to established biomarkers, thus perhaps assisting in management of axial SpA.
本研究旨在评估中性粒细胞与淋巴细胞比值(NLR)和血小板与淋巴细胞比值(PLR)在预测轴性脊柱关节炎(SpA)放射学骶髂关节炎和活动性疾病方面的效用,并探讨与传统炎症标志物相比,使用肿瘤坏死因子抑制剂(TNFi)与这些实验室值之间的关系。
对理解 SpA 长期结局计划(PULSAR)登记处的观察性数据进行了分析。我们生成了受试者工作特征曲线以计算实验室截断值;我们使用这些值在多变量逻辑回归模型中识别与放射学证实的骶髂关节炎和活动性疾病的关联。我们还使用逻辑回归来确定 TNFi 起始后实验室值升高的可能性。
大多数研究参与者(n=354)为白人、男性且 HLA-B27 阳性。NLR(比值比[OR]1.459,P=0.034)、PLR(OR 4.842,P<0.001)、红细胞沉降率(OR 4.397,P<0.001)和 C 反应蛋白(CRP)水平(OR 2.911,P=0.001)是放射学骶髂关节炎的独立预测因子。包含 PLR 与传统生物标志物的模型比仅包含传统生物标志物的模型表现更好。NLR(OR 6.931,P=0.002)和 CRP(OR 2.678,P=0.004)是活动性疾病的预测因子,但包含 NLR 和 CRP 的模型比仅包含 CRP 的模型表现更好。TNFi 的使用降低了 NLR 升高的可能性(OR 0.172,P<0.001)、PLR(OR 0.073,P<0.001)、红细胞沉降率(OR 0.319,P<0.001)和 CRP(OR 0.407,P<0.001),但包含 NLR 或 PLR 和传统生物标志物的模型表现最佳。
这些发现表明 NLR 和 PLR 与骶髂关节炎和疾病活动度之间存在关联,并且 NLR 和 PLR 在 TNFi 治疗后显示出反应,并为既定生物标志物提供了有用的临床信息,从而可能有助于管理轴性 SpA。