Clinical value of neutrophil-to-lymphocyte ratio in patients with non-small-cell lung cancer treated with PD-1/PD-L1 inhibitors
- PMID: 30885355
- DOI: 10.1016/j.lungcan.2019.02.009
Clinical value of neutrophil-to-lymphocyte ratio in patients with non-small-cell lung cancer treated with PD-1/PD-L1 inhibitors
Abstract
Introduction: There is unmet need to explore the predictive biomarkers of PD-1/PD-L1 inhibitors in patients with non-small-cell lung cancer (NSCLC). Here, we aimed to investigate the predictive and prognostic value of blood neutrophil-to-lymphocyte ratio (NLR) in NSCLC patients treated with PD-1/PD-L1 inhibitors.
Methods: We performed a comprehensive online search to explore the association between blood NLR and overall survival (OS) or progression-free survival (PFS) in NSCLC patients received PD-1/PD-L1 inhibitors. Published data including hazard ratios (HRs) and 95% confidence interval (CI) were eligible. Pooled estimates of treatment outcomes were calculated using Stata/MP 14.1.
Results: 1700 patients from sixteen studies were included. The pooled results suggested that high blood NLR was correlated with significantly shorter OS (HR = 2.07, P < 0.001) and PFS (HR = 1.59, P < 0.001). The predictive and prognostic significance of blood NLR were observed consistently across most subgroups including publication year, study design, research region, PD-L1 expression detection, sample size, NLR cutoff, median follow-up time and study quality score. Additionally, there was a significant correlation between elevated NLR cutoff values and OS benefit (r = 0.585, P = 0.036) but not for PFS benefit (r = 0.198, P = 0.496). Notably, HRs of PFS showed significant correlation with HRs of OS (r = 0.686, P = 0.041).
Conclusion: Elevated blood NLR was associated with shorter PFS and OS in NSCLC patients treated with PD-1/PD-L1 inhibitors, suggesting its potential predictive and prognostic value in this clinical scenario.
Keywords: Biomarker; Neutrophil-to-lymphocyte ratio; Non-small-cell lung cancer; PD-1; PD-L1.
Copyright © 2019 Elsevier B.V. All rights reserved.
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