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Dynamics of neutrophils to lymphocyte ratio (NLR) predict outcomes of PD-1/PD-L1 blockade

Forster, MD; Moschetta, M; Uccello, M; Kasenda, B; Mak, G; McClelland, A; Boussios, S; (2017) Dynamics of neutrophils to lymphocyte ratio (NLR) predict outcomes of PD-1/PD-L1 blockade. BioMed Research International , 2017 , Article 1506824. 10.1155/2017/1506824. Green open access

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Abstract

Introduction. Baseline neutrophil-to-lymphocyte ratio (NLR) has been repeatedly reported as a significant prognostic factor in advanced cancer patients. We explored whether changes in NLR may predict outcome of advanced cancer patients enrolled into phase 1 trials and treated with PD-1/PD-L1 inhibitors. Patients and Methods. Advanced cancer patients enrolled into phase 1 trials between September 2013 and May 2016 and treated with anti-PD-1/PD-L1 agents were included in this retrospective study. NLR was calculated at baseline and after 2 cycles of treatment. Royal Marsden Hospital (RMH) prognostic score and Eastern Cooperative Group (ECOG) performance status (PS) were determined at baseline. Kaplan-Meier estimation and Cox regression analyses were used to assess the impact of NLR dynamics on PFS. Results. Among the 55 patients eligible, 26 (47%) were treated with anti-PD-L1 monotherapy, 22 (40%) received single agent anti-PD-1, and 7 (13%) were given a tyrosine kinase inhibitor (TKI) plus a PD-1 inhibitor. Neither ECOG PS nor RMH prognostic score was significantly associated with PFS in our cohort, whereas changes in NLR significantly impacted on PFS. Conclusion. Changes in the NLR may be a useful predicting factor in advanced cancer patients treated with anti-PD-1/PD-L1 agents. Further prospective trials are needed to verify these findings.

Type: Article
Title: Dynamics of neutrophils to lymphocyte ratio (NLR) predict outcomes of PD-1/PD-L1 blockade
Open access status: An open access version is available from UCL Discovery
DOI: 10.1155/2017/1506824
Publisher version: http://doi.org/10.1155/2017/1506824
Language: English
Additional information: Copyright © 2017 Michele Moschetta et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Oncology
URI: https://discovery.ucl.ac.uk/id/eprint/10040095
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