title: Fine-tuning of the prediction of mortality in hemodialysis patients by use of cytokine proteomic determination.
abstract: OBJECTIVE
  Inflammation-induced atherosclerosis and enhanced susceptibility to infection are linked to immune dysfunction and account for an important part of mortality in hemodialysis patients. This 4-yr prospective study aimed to use cytokine proteomic determination for predicting cardiovascular and noncardiovascular mortality in hemodialysis patients.
  
  
  METHODS
  Levels of 12 cytokines were measured using a proteomic biochip system in 134 patients who were on stable hemodialysis and compared with a control group of 150 healthy volunteers. Cox proportional hazards regression analysis was used to determine the relationship between cytokine and clinical outcome.
  
  
  RESULTS
  A proinflammatory state characterized by decreased anti-/proinflammatory cytokine ratio was evidenced in hemodialysis patients compared with control subjects. After adjustment for age, gender, smoking, and high-sensitivity C-reactive protein levels, IL-6 and (IL-4+IL-10)/IL-6 ratio were associated with a significant and specific enhanced hazard ratio of cardiovascular mortality (hazard ratio 11.32 [95% confidence interval 2.52 to 50.90; P < 0.01] and hazard ratio 3.14 [95% confidence interval 1.20 to 8.22; P < 0.05], respectively, when comparing the third and first tertiles). It is interesting that (IL-4+IL-6+IL-10)/(IL-2+IFN-gamma) ratio, used as a marker of lymphocytes T helper subsets cytokine secretion, was associated only with noncardiovascular mortality (hazard ratio 4.93; 95% confidence interval 1.03 to 23.65; P < 0.05).
  
  
  CONCLUSIONS
  Beyond the strong prediction of cardiovascular mortality by IL-6, determination of cytokine ratios can be useful to identify hemodialysis patients with increased noncardiovascular mortality risk.
authors.affiliation: Biochemistry Laboratory, Lapeyronie University Hospital, 371 Avenue Doyen Gaston Giraud, F34295 Montpellier Cedex 5, France.
authors.forename: Stéphanie
authors.initials: S
authors.lastname: Badiou
authors.forename: Jean-Paul
authors.initials: JP
authors.lastname: Cristol
authors.forename: Isabelle
authors.initials: I
authors.lastname: Jaussent
authors.forename: Nathalie
authors.initials: N
authors.lastname: Terrier
authors.forename: Marion
authors.initials: M
authors.lastname: Morena
authors.forename: François
authors.initials: F
authors.lastname: Maurice
authors.forename: Hélène
authors.initials: H
authors.lastname: Leray-Moragues
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Rivory
authors.forename: Lofti
authors.initials: L
authors.lastname: Chalabi
authors.forename: Cécile
authors.initials: C
authors.lastname: Delcourt
authors.forename: Bernard
authors.initials: B
authors.lastname: Canaud
authors.forename: Anne-Marie
authors.initials: AM
authors.lastname: Dupuy
mesh_terms: D000368:Aged; D002318:Cardiovascular Diseases / Q000097:blood* / Q000453:epidemiology*; D016207:Cytokines / Q000097:blood*; D005260:Female; D006801:Humans; D007676:Kidney Failure, Chronic / Q000097:blood* / Q000401:mortality* / Q000628:therapy*; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D011446:Prospective Studies; D040901:Proteomics; D006435:Renal Dialysis / Q000401:mortality*
chemical_list: D016207:Cytokines