Background: Neutrophil-to-Lymphocyte Ratio (NLR) and derived Neutrophils-to-(Leukocytes minus neutrophils) Ratio (dNLR) have been proposed as possible biomarkers of response to immune checkpoint inhibitors (ICI). However, in non-small cell lung cancer (NSCLC) studies, various NLR and/or dNLR cut-offs have been used, manly based on previous reports on melanoma. Methods: In this Italian multicenter retrospective study, NLR, dNLR, platelet-to-lymphocyte ratio, albumin, and lactate dehydrogenase (LDH) were longitudinally assessed in patients with stage IV non-small cell lung cancer (NSCLC) treated with ICI. The primary objective was to evaluate if baseline parameters predicted response to ICI, using Receiver Operating Characteristic (ROC) curves. Secondary endpoint was to evaluate if dynamic changing of NLR and dNLR also predicted response. Results: Data of 402 patients were collected and analyzed. Among the baseline parameters considered, NLR and dNLR were the most appropriate biomarkers according to the ROC analyses, which also identified meaningful cut-offs (NLR = 2.46; dNLR = 1.61). Patients with low ratios reported a significantly improved outcome, in terms of overall survival (p = 0.0003 for NLR; p = 0.0002 for dNLR) and progression free survival (p = 0.0004 for NLR; p = 0.005 for dNLR). The role of NLR and dNLR as independent biomarkers of response was confirmed in the Cox regression model. When assessing NLR and dNLR dynamics from baseline to cycle 3, a decrease ≥1.04 for NLR and ≥0.41 for dNLR also predicted response. Conclusions in our cohort, we confirmed that NLR and dNLR, easily assessable on peripheral blood, can predict response at baseline and early after ICI initiation. For both baseline and dynamic assessment, we identified clinically meaningful cut-offs, using ROC curves

ROC Analysis Identifies Baseline and Dynamic NLR and dNLR Cut-Offs to Predict ICI Outcome in 402 Advanced NSCLC Patients

Annapaola Mariniello;Tiziana Vavalà;Ilaria Stura;Fabrizio Tabbò;Giuseppe Migliaretti;Silvia Novello
2020-01-01

Abstract

Background: Neutrophil-to-Lymphocyte Ratio (NLR) and derived Neutrophils-to-(Leukocytes minus neutrophils) Ratio (dNLR) have been proposed as possible biomarkers of response to immune checkpoint inhibitors (ICI). However, in non-small cell lung cancer (NSCLC) studies, various NLR and/or dNLR cut-offs have been used, manly based on previous reports on melanoma. Methods: In this Italian multicenter retrospective study, NLR, dNLR, platelet-to-lymphocyte ratio, albumin, and lactate dehydrogenase (LDH) were longitudinally assessed in patients with stage IV non-small cell lung cancer (NSCLC) treated with ICI. The primary objective was to evaluate if baseline parameters predicted response to ICI, using Receiver Operating Characteristic (ROC) curves. Secondary endpoint was to evaluate if dynamic changing of NLR and dNLR also predicted response. Results: Data of 402 patients were collected and analyzed. Among the baseline parameters considered, NLR and dNLR were the most appropriate biomarkers according to the ROC analyses, which also identified meaningful cut-offs (NLR = 2.46; dNLR = 1.61). Patients with low ratios reported a significantly improved outcome, in terms of overall survival (p = 0.0003 for NLR; p = 0.0002 for dNLR) and progression free survival (p = 0.0004 for NLR; p = 0.005 for dNLR). The role of NLR and dNLR as independent biomarkers of response was confirmed in the Cox regression model. When assessing NLR and dNLR dynamics from baseline to cycle 3, a decrease ≥1.04 for NLR and ≥0.41 for dNLR also predicted response. Conclusions in our cohort, we confirmed that NLR and dNLR, easily assessable on peripheral blood, can predict response at baseline and early after ICI initiation. For both baseline and dynamic assessment, we identified clinically meaningful cut-offs, using ROC curves
2020
19
31
NSCLC; immunotherapy; biomarkers; NLR; dNLR
Simona Carnio, Annapaola Mariniello, Pamela Pizzutilo, Gianmauro Numico, Gloria Borra, Alice Lunghi, Hector Soto Parra, Roberta Buosi, Tiziana Vavalà, Ilaria Stura, Silvia Genestroni, Alessandra Alemanni, Francesca Arizio, Annamaria Catino, Michele Montrone, Fabrizio Tabbò, Domenico Galetta, Giuseppe Migliaretti, Silvia Novello
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1770494
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