The time-series behavior of neutrophil-to-lymphocyte ratio is useful as a predictive marker in non-small cell lung cancer.

• Main Authors: Tatsunori Kiriu, Masatsugu Yamamoto, Tatsuya Nagano, Daisuke Hazama, Reina Sekiya, Masahiro Katsurada, Daisuke Tamura, Motoko Tachihara, Kazuyuki Kobayashi, Yoshihiro Nishimura
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2018-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC5814002?pdf=render

Nivolumab improves the survival of advanced non-small cell lung cancer (NSCLC), but a significant number of patients still fail to benefit from this treatment. In this study, we evaluated the efficacy of the time-series behavior of neutrophil-to-lymphocyte ratio (NLR) in a complete blood count from advanced NSCLC patients as a predictive marker of the anticancer effect of nivolumab.We performed a retrospective review of medical records and collected data on patients with advanced NSCLC treated with nivolumab as second- and further-line treatments from December 2015 to March 2017. The NLRs were calculated before each treatment cycle for four cycles. These parameters were tested for its association with the overall survival (OS), progression-free survival (PFS) and time to treatment failure (TTF).Nineteen patients were treated with nivolumab. Stratified by the response to nivolumab, the median OS was 2.8 months in progressive disease (PD) and 14.0 months in non-PD (p = 0.002). Before discontinuation of PD or toxicity, an NLR is rising from baseline in 5 out of 7 patients with PD and all of 4 patients with discontinuation due to toxicity. Patients with an >30% increase in NLR were associated with a significantly shorter TTF compared with those with stable or decrease in NLR both after first cycle (p = 0.014) and second cycle (p < 0.001).The NLR is suggested to be useful not only as a prognostic marker but also as a predictive marker for treatment with nivolumab. Further prospective study is warranted to develop a predictive algorithm to detect PD cases as early as possible by focusing the time-series behavior of NLR.