title: C-reactive protein and prediction of 1-year mortality in prevalent hemodialysis patients.
abstract: OBJECTIVE
  Measurement of C-reactive protein (CRP) levels remains uncommon in North America, although it is now routine in many countries. Using Dialysis Outcomes and Practice Patterns Study data, our primary aim was to evaluate the value of CRP for predicting mortality when measured along with other common inflammatory biomarkers.
  
  
  METHODS
  We studied 5061 prevalent hemodialysis patients from 2005 to 2008 in 140 facilities routinely measuring CRP in 10 countries. The association of CRP with mortality was evaluated using Cox regression. Prediction of 1-year mortality was assessed in logistic regression models with differing adjustment variables.
  
  
  RESULTS
  Median baseline CRP was lower in Japan (1.0 mg/L) than other countries (6.0 mg/L). CRP was positively, monotonically associated with mortality. No threshold below which mortality rate leveled off was identified. In prediction models, CRP performance was comparable with albumin and exceeded ferritin and white blood cell (WBC) count based on measures of model discrimination (c-statistics, net reclassification improvement [NRI]) and global model fit (generalized R(2)). The primary analysis included age, gender, diabetes, catheter use, and the four inflammatory markers (omitting one at a time). Specifying NRI ≥5% as appropriate reclassification of predicted mortality risk, NRI for CRP was 12.8% compared with 10.3% for albumin, 0.8% for ferritin, and <0.1% for WBC.
  
  
  CONCLUSIONS
  These findings demonstrate the value of measuring CRP in addition to standard inflammatory biomarkers to improve mortality prediction in hemodialysis patients. Future studies are indicated to identify interventions that lower CRP and to identify whether they improve clinical outcomes.
authors.affiliation: Arbor Research Collaborative for Health, Ann Arbor, Michigan, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Bazeley
authors.forename: Brian
authors.initials: B
authors.lastname: Bieber
authors.forename: Yun
authors.initials: Y
authors.lastname: Li
authors.forename: Hal
authors.initials: H
authors.lastname: Morgenstern
authors.forename: Patricia
authors.initials: P
authors.lastname: de Sequera
authors.forename: Christian
authors.initials: C
authors.lastname: Combe
authors.forename: Hiroyasu
authors.initials: H
authors.lastname: Yamamoto
authors.forename: Martin
authors.initials: M
authors.lastname: Gallagher
authors.forename: Friedrich K
authors.initials: FK
authors.lastname: Port
authors.forename: Bruce M
authors.initials: BM
authors.lastname: Robinson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001315:Australia; D015415:Biomarkers / Q000097:blood; D002097:C-Reactive Protein / Q000032:analysis*; D005060:Europe; D005260:Female; D006801:Humans; D018836:Inflammation Mediators / Q000097:blood*; D007564:Japan; D007674:Kidney Diseases / Q000175:diagnosis* / Q000276:immunology / Q000401:mortality* / Q000628:therapy; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009520:New Zealand; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies; D006435:Renal Dialysis / Q000401:mortality*; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome; D014481:United States; D055815:Young Adult
chemical_list: D015415:Biomarkers; D018836:Inflammation Mediators; D002097:C-Reactive Protein