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

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Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
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Clinical Cancer Center “Giovanni Paolo II”, 70124 Bari, Italy
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Oncology Unit, Alessandria Hospital, 15121 Alessandria, Italy
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Company Hospital-University Major of Charity of Novara, 28100 Novara, Italy
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Department of Oncology, Division of Oncology, S. Luca Hospital, 55100 Lucca, Italy
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Medical Oncology Unit, AOU Policlinico-Vittorio Emanuele, 95123 Catania, Italy
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Department of Medical Oncology, Santo Spirito Hospital, 15033 Casale Monferrato, Italy
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SC of Oncology Ospedale Civile di Saluzzo, ASL CN1, 12037 Saluzzo, Italy
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Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, 10126 Torino, Italy
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Clinical Trials Unit of Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
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Author to whom correspondence should be addressed.
J. Mol. Pathol. 2020, 1(1), 19-31; https://doi.org/10.3390/jmp1010004
Received: 4 August 2020 / Revised: 26 August 2020 / Accepted: 10 September 2020 / Published: 15 September 2020
(This article belongs to the Special Issue Molecular Pathology in Solid Tumors)
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. View Full-Text
Keywords: NSCLC; immunotherapy; biomarkers; NLR; dNLR NSCLC; immunotherapy; biomarkers; NLR; dNLR
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Carnio, S.; Mariniello, A.; Pizzutilo, P.; Numico, G.; Borra, G.; Lunghi, A.; Soto Parra, H.; Buosi, R.; Vavalà, T.; Stura, I.; Genestroni, S.; Alemanni, A.; Arizio, F.; Catino, A.; Montrone, M.; Tabbò, F.; Galetta, D.; Migliaretti, G.; Novello, S. ROC Analysis Identifies Baseline and Dynamic NLR and dNLR Cut-Offs to Predict ICI Outcome in 402 Advanced NSCLC Patients. J. Mol. Pathol. 2020, 1, 19-31.

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