Neutrophil/lymphocyte ratio has a prognostic value for patients with terminal cancer. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Nakamura, Yoichi; Watanabe, Ryohei; Katagiri, Miwa; Saida, Yoshihisa; Katada, Natsuya; Watanabe, Manabu; Okamoto, Yasushi; Asai, Koji; Enomoto, Toshiyuki; Kiribayashi, Takaharu; Kusachi, Shinya
• Is Part Of: World journal of surgical oncology. Volume 14:Issue 1(2016)
• Page Start: 1
• Page End: 5
• Publication Date: 2016-12
• Subjects: Blood cells -- Inflammation -- Neoplasms -- Palliative care -- Prognosis; Cancer -- Surgery -- Periodicals; Tumors -- Periodicals; Tumors -- Surgery -- Periodicals; Surgery, Operative -- Periodicals; 616.994059
• DOI: 10.1186/s12957-016-0904-7
• Languages: English
• ISSNs: 1477-7819

Abstract

Abstract Background Determining prognosis in advanced cancer is of key importance. Various prognostic scores have been developed. However, they are often very complex. In this study, we evaluated the feasibility of neutrophil/lymphocyte ratio (NLR) as an index to estimate survival in terminal cancer patients. Methods NLR was calculated retrospectively based on blood tests performed at 3 months, 2 months, 4 weeks, 3 weeks, 2 weeks, 1 week, and within 3 days before death in 160 cancer patients (82 men, 78 women; age range, 33–99 years; mean age, 69.8 years). Results NLR increased significantly with time (P < 0.0001). Mean NLR was significantly higher in patients who died within 4 weeks (29.82) than in those who lived more than 4 weeks (6.15). The NLR cutoff point was set at 9.21 according to receiver operating characteristic curve analysis (area under the curve, 0.82; 95 % confidence interval, 0.79–0.85). We inferred that life expectancy would be <4 weeks when NLR >9.21. The sensitivity, specificity, positive predictive value, and negative predictive value were 65.6, 84.1, 90.6, and 51.1 %, respectively. The positive and negative likelihood ratios were 4.125 and 0.409, respectively. Conclusions NLR appears to be a useful and simple parameter to predict the clinical outcomes of patients with terminal cancer.