title: Neutrophil-lymphocyte ratio as a novel predictor of survival in chronic hemodialysis patients.
abstract: BACKGROUND
  Increased mortality rate in chronic hemodialysis (HD) patients is partly attributed to a chronic inflammatory state. Neutrophil-lymphocyte ratio (NLR), defined as the neutrophil count divided by lymphocyte count, is increasingly recognized as a marker of systemic inflammation, but its prognostic value in HD patients is unknown. The aim of this study was to assess NLR as a predictor of survival in this patient population.
  
  
  METHODS
  In this study incident chronic HD patients were stratified in tertiles of NLR based on measurements obtained 3 months after initiation of dialysis. Multivariable Cox regression was used to calculate the adjusted hazard ratios (HR) for NLR on all-cause survival. Subsequently, similar models were developed at years 2 and 3 to assess predictive value of NLR in prevalent patients.
  
  
  RESULTS
  We studied 5,782 incident HD patients (mean ± SD age 62 ± 15 years, 55% male, 43% Black, 52% diabetic). The median (interquartile, (IQR)) NLR at 3 months was 3.0 (2.1 - 4.5). NLR in the highest tertile (NLR ≥ 3.9) was a significant predictor of all-cause mortality after an adjustment for demographic and clinical covariates was performed. These results were confirmed at years 2 and 3. Moreover, NLR is superior to total white blood cell (WBC) count for prediction of all-cause mortality in incident hemodialysis patients (are under the receiver operating characteristic (ROC) curve of 0.66 vs. 0.56).
  
  
  CONCLUSIONS
  This study identifies NLR as a novel and robust predictor of all-cause mortality in incident and prevalent HD patients. NLR is an inexpensive and readily available marker that may help to identify HD patients who are at an increased risk of death.
authors.forename: Georges
authors.initials: G
authors.lastname: Ouellet
authors.forename: Rakesh
authors.initials: R
authors.lastname: Malhotra
authors.forename: E Lars
authors.initials: EL
authors.lastname: Penne
authors.forename: Len
authors.initials: L
authors.lastname: Usvya
authors.forename: Nathan W
authors.initials: NW
authors.lastname: Levin
authors.forename: Peter
authors.initials: P
authors.lastname: Kotanko
mesh_terms: D001741:Black or African American / Q000706:statistics & numerical data; D000368:Aged; D015415:Biomarkers / Q000097:blood; D015897:Comorbidity; D003920:Diabetes Mellitus / Q000453:epidemiology; D005260:Female; D005544:Forecasting; D006801:Humans; D007249:Inflammation / Q000276:immunology; D007958:Leukocyte Count; D018655:Lymphocyte Count; D008214:Lymphocytes / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D017202:Myocardial Ischemia / Q000453:epidemiology; D009504:Neutrophils / Q000473:pathology*; D009519:New York City / Q000453:epidemiology; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve; D006435:Renal Dialysis / Q000401:mortality* / Q000706:statistics & numerical data; D012680:Sensitivity and Specificity; D015996:Survival Rate; D044465:White People / Q000706:statistics & numerical data
chemical_list: D015415:Biomarkers