TY - JOUR
T1 - Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio as Biomarkers in Axial Spondyloarthritis
T2 - Observational Studies From the Program to Understand the Longterm Outcomes in Spondyloarthritis Registry
AU - Sen, Rouhin
AU - Kim, Emmeline
AU - Napier, Ruth J.
AU - Cheng, Elizabeth
AU - Fernandez, Andrea
AU - Manning, Evan S.
AU - Anderson, Eric R.
AU - Maier, Kyle D.
AU - Hashim, Mena
AU - Kerr, Gail S.
AU - Fang, Meika A.
AU - Hou, Jason K.
AU - Chang, Elizabeth
AU - Walsh, Jessica A.
AU - Raychadhuri, Siba P.
AU - Reimold, Andreas
AU - Caplan, Liron
N1 - Publisher Copyright:
© 2022 American College of Rheumatology. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
PY - 2023/2
Y1 - 2023/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85145042031&partnerID=8YFLogxK
U2 - 10.1002/art.42333
DO - 10.1002/art.42333
M3 - Article
C2 - 36053919
AN - SCOPUS:85145042031
SN - 2326-5191
VL - 75
SP - 232
EP - 241
JO - Arthritis and Rheumatology
JF - Arthritis and Rheumatology
IS - 2
ER -