Neutrophil-to-lymphocyte ratio as a biomarker for disease onset and mortality risk in systemic sclerosis: a real-world national cohort study

作者
Shiri Keret,Shlomit Yaari,Aniela Shouval,Alaa Sawaed,Noa Nemesh,Lisa Kaly,Abid Awisat,Itzhak Rosner,Michael Rozenbaum,Nina Boulman,Emilia Hardak,Gleb Slobodin,Doron Rimar
出处
期刊:Rheumatology [Oxford University Press]
标识
DOI:10.1093/rheumatology/keaf664
摘要

Abstract Objectives Elevated neutrophil-to-lymphocyte ratio (NLR)≥2.95 has been linked to adverse outcomes in systemic sclerosis (SSc). This study aimed to determine whether elevated NLR can signal disease onset, identify NLR threshold predictive of poor prognosis, and describe its longitudinal variations. Methods Adult SSc patients from Maccabi Healthcare Services were identified between 1998-2023 using ICD-9 diagnosis codes of SSc and the presence of serological confirmation. Results Of 1,752 patients meeting inclusion criteria, 241 were excluded due to steroid use, yielding 1,511 patients, of whom 1,232 had baseline NLR data. The mean NLR at diagnosis was 2.2±1.4. Among patients with baseline NLR≥3 (n = 191, mean 4.4±2.2), NLR increased significantly at disease onset compared to 1-15 years prior (p < 0.01). Following diagnosis, NLR remained persistently elevated over 15 years, unaffected by treatment. Kaplan-Meier curves stratification into 4 NLR categories (0-1.99, 2.00-2.99, 3.00-3.99, ≥4.0) revealed a clear stepwise decline in 5 and 10 survival with increasing NLR (log-rank p < 0.001). In multivariable Cox regression, adjusted for age, sex, interstitial lung disease, and pulmonary hypertension, NLR≥ 3 and to a further extent ≥4 were both independently associated with mortality (HR 1.7, p = 0.025 and HR 2.8, p < 0.001, respectively). Conclusion Our study suggests that an increase in NLR marks the onset of disease in a subset of SSc patients with poor outcomes. An NLR value above 4 at diagnosis identifies patients at high risk for mortality. NLR is a simple and cost-effective prognostic biomarker that may be used to identify high-risk patients who would benefit from early and intensive treatment.
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