Neutrophil‐to‐Lymphocyte Ratio and Platelet‐to‐Lymphocyte Ratio as Biomarkers in Axial Spondyloarthritis: Observational Studies From the Program to Understand the Longterm Outcomes in Spondyloarthritis Registry

• Published in: Arthritis & rheumatology (Hoboken, N.J.) Vol. 75; no. 2; pp. 232 - 241
• Main Authors: Sen, Rouhin, Kim, Emmeline, Napier, Ruth J., Cheng, Elizabeth, Fernandez, Andrea, Manning, Evan S., Anderson, Eric R., Maier, Kyle D., Hashim, Mena, Kerr, Gail S., Fang, Meika A., Hou, Jason K., Chang, Elizabeth, Walsh, Jessica A., Raychadhuri, Siba P., Reimold, Andreas, Caplan, Liron
• Format: Journal Article
• Language: English
• Published: Boston, USA Wiley Periodicals, Inc 01.02.2023; Wiley Subscription Services, Inc
• Subjects: Arthritis; Axial Spondyloarthritis; Biomarkers; Blood Platelets; Erythrocyte sedimentation rate; Erythrocytes; Humans; Inflammation; Inflammatory diseases; Laboratories; Leukocytes (neutrophilic); Lymphocytes; Male; Neutrophils; Observational studies; Platelets; Pulsars; Regression analysis; Regression models; Retrospective Studies; Rheumatic diseases; Sacroiliitis; Spondylarthritis - drug therapy
• ISSN: 2326-5191; 2326-5205; 2326-5205
• DOI: 10.1002/art.42333

Objectives 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. Methods 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. Results 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. Conclusions 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.