Role of Monocyte Count and Neutrophil-to- Lymphocyte Ratio in Survival of Oral Cancer Patients

• Autor(a) principal: Bobdey,Saurabh
• Data de Publicação: 2017
• Outros Autores: Ganesh,Balasubramaniam, Mishra,Prabhashankar, Jain,Aanchal
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: International Archives of Otorhinolaryngology
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1809-48642017000100021
• topic: oral cancer; prognosis; survival; monocyte; neutrophil-tolymphocyte ratio

Abstract Introduction Inflammation seems to play a critical role in the development and progression of numerous cancers. Peripheral blood leukocyte count is an easily assessable parameter of systemic inflammatory response. Objective The aim of this study was to investigate whether the pretreatment leukocyte counts can predict the prognosis of patients with oral cavity cancer. Methods Medical records of 471 oral cavity cancer patients diagnosed between January 2007 and December 2008 were retrospectively analyzed. Receiver operating characteristic curve analysis and Cox proportional hazards analyses were applied to evaluate the associations of leukocyte counts with overall survival. Results The overall five year's survival of the cohort was found to be 49.4%. On univariate analysis, elevated monocyte count (≥500/mm3) and neutrophil-to-lymphocyte ratio (NLR) (>2.38) were associated with poor overall survival (OS) (p = 0.001 and 0.000, respectively). Multivariate Cox proportional hazard analysis showed that higher monocyte and NLR levels were significant independent predictors of worse OS (HR = 1.385, 95% CI = 1.049 - 1.829; p < 0.05 and HR = 1.392, 95% CI = 1.045 - 1.855; p < 0.05, respectively). The advanced overall stage and lymph nodal involvement were also independent indicators for poor OS. Conclusions Higher pretreatment monocyte and NLR levels are independent predictors of poor prognosis for patients with oral cavity cancer. Thus, these easily accessed variables can serve as a potent marker to predict the outcomes of oral cancer patients.