title: Predicting potential survival benefit of renal transplantation in patients with chronic kidney disease.
abstract: BACKGROUND
  To facilitate decision-making about treatment options for patients with end-stage renal disease considering kidney transplantation, we sought to develop an index for clinical prediction of risk for death.
  
  
  METHODS
  We derived and validated a multivariable survival model predicting time to death in 169,393 patients with end-stage renal disease who were eligible for transplantation. We modified the model into a simple point-system index.
  
  
  RESULTS
  Deaths occurred in 23.5% of the cohort. Twelve variables independently predicted death: age, race, cause of kidney failure, body mass index, comorbid disease, smoking, employment status, serum albumin level, year of first renal replacement therapy, kidney transplantation, time to transplant wait-listing and time on the wait list. The index separated patients into 26 groups having significantly unique five-year survival, ranging from 97.8% in the lowest-risk group to 24.7% in the highest-risk group. The index score was discriminative, with a concordance probability of 0.746 (95% CI 0.741-0.751). Observed survival in the derivation and validation cohorts was similar for each level of index score in 93.9% of patients.
  
  
  CONCLUSIONS
  Our prognostic index uses commonly available information to predict mortality accurately in patients with end-stage renal disease. This index could provide valuable quantitative data on survival for clinicians and patients to use when deciding whether to pursue transplantation or remain on dialysis.
authors.affiliation: Faculty of Medicine, University of Ottawa, Ont. carlv@ohri.ca
authors.forename: Carl
authors.initials: C
authors.lastname: van Walraven
authors.forename: Peter C
authors.initials: PC
authors.lastname: Austin
authors.forename: Greg
authors.initials: G
authors.lastname: Knoll
mesh_terms: D000367:Age Factors; D015992:Body Mass Index; D015897:Comorbidity; D003627:Data Interpretation, Statistical; D004651:Employment; D005260:Female; D006801:Humans; D007676:Kidney Failure, Chronic / Q000401:mortality* / Q000628:therapy; D016030:Kidney Transplantation; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009010:Monte Carlo Method; D011379:Prognosis; D044469:Racial Groups; D012044:Regression Analysis; D017582:Renal Replacement Therapy; D018570:Risk Assessment; D012709:Serum Albumin; D012907:Smoking; D016019:Survival Analysis; D013997:Time Factors; D014481:United States; D014850:Waiting Lists
chemical_list: D012709:Serum Albumin