P1.04-61 Neutrophil-Lymphocyte Ratio: A Predictive Biomarker of Immunotherapy in Lung Cancer?

Abstract

Identifying predictive biomarkers of immunotherapy in advanced non-small cell lung cancer (NSCLC) is essential to select the patients that could benefit more from this revolutionary therapy. Besides PD-L1 expression, neutrophil-lymphocyte ratio (NLR) has been explored as a potential predictor of clinically meaningful outcomes. Aim: Assess if NLR is an independent predictor of response to immunotherapy in advanced NSCLC. Retrospective study of patients with locally advanced or metastatic NSCLC treated with immunotherapy in the second or further lines setting in a Multidisciplinary Thoracic Tumor Unit between 2015 and 2018. Pre-treatment NLR was calculated from baseline peripheral blood cell counts. NLR was categorized as a binary variable: “low” (<5) or “high” (≥5). Cox regression models were used for overall survival (OS) and progression-free survival (PFS) analysis. From a total of 63 patients, 49 were treated with nivolumab and 14 with pembrolizumab. At the beginning of immunotherapy, baseline patient characteristics were: men: 79.4%; median age (IQR): 62 (56-70) years; ever smokers: 82.5%; ECOG PS 0-1: 82.5%; adenocarcinoma: 63.5%; squamous cell carcinoma: 31.7% and NSCLC-NOS: 4.8%; stage IV: 76.2%; PD-L1 expression <1%: 47.6%. Twenty-three patients (36.5%) received immunotherapy in the third or further lines of treatment. Median PFS and OS were 5 months (2-10) and 8 months (4-13), respectively. After adjusting for gender, age, tobacco habits, ECOG PS, histology and PD-L1 expression, "high" NLR was an independent predictive factor of worse PFS (HR 2.22; 95% CI 1.06-4.66; p 0.035) and OS (HR 2.74; 95% CI 1.19-6.30; p 0.017). In our cohort, patients with NLR≥5 had a higher risk of disease progression and death compared to those with NLR<5. NLR is an inexpensive and affordable biomarker that could help to predict response to immunotherapy. Further large prospective studies are needed to validate this biomarker and to establish the optimal cut-off level.