title: Predicting mortality in incident dialysis patients: an analysis of the United Kingdom Renal Registry.
abstract: BACKGROUND
  The risk of death in dialysis patients is high, but varies significantly among patients. No prediction tool is used widely in current clinical practice. We aimed to predict long-term mortality in incident dialysis patients using easily obtainable variables.
  
  
  METHODS
  Prospective nationwide multicenter cohort study in the United Kingdom (UK Renal Registry); models were developed using Cox proportional hazards.
  
  
  METHODS
  Patients initiating hemodialysis or peritoneal dialysis therapy in 2002-2004 who survived at least 3 months on dialysis treatment were followed up for 3 years. Analyses were restricted to participants for whom information for comorbid conditions and laboratory measurements were available (n = 5,447). The data set was divided into data sets for model development (n = 3,631; training) and validation (n = 1,816) using random selection.
  
  
  METHODS
  Basic patient characteristics, comorbid conditions, and laboratory variables.
  
  
  RESULTS
  All-cause mortality censored for kidney transplant, recovery of kidney function, and loss to follow-up.
  
  
  RESULTS
  In the training data set, 1,078 patients (29.7%) died within the observation period. The final model for the training data set included patient characteristics (age, race, primary kidney disease, and treatment modality), comorbid conditions (diabetes, history of cardiovascular disease, and smoking), and laboratory variables (hemoglobin, serum albumin, creatinine, and calcium levels); reached a C statistic of 0.75 (95% CI, 0.73-0.77); and could discriminate accurately among patients with low (6%), intermediate (19%), high (33%), and very high (59%) mortality risk. The model was applied further to the validation data set and achieved a C statistic of 0.73 (95% CI, 0.71-0.76).
  
  
  CONCLUSIONS
  Number of missing comorbidity data and lack of an external validation data set.
  
  
  CONCLUSIONS
  Basic patient characteristics, comorbid conditions, and laboratory variables can predict 3-year mortality in incident dialysis patients with sufficient accuracy. Identification of subgroups of patients according to mortality risk can guide future research and subsequently target treatment decisions in individual patients.
authors.affiliation: Department of Medicine, Division of Nephrology, Tufts Medical Center, Boston, MA, USA. wagner_m@klinik.uni-wuerzburg.de
authors.forename: Martin
authors.initials: M
authors.lastname: Wagner
authors.forename: David
authors.initials: D
authors.lastname: Ansell
authors.forename: David M
authors.initials: DM
authors.lastname: Kent
authors.forename: John L
authors.initials: JL
authors.lastname: Griffith
authors.forename: David
authors.initials: D
authors.lastname: Naimark
authors.forename: Christoph
authors.initials: C
authors.lastname: Wanner
authors.forename: Navdeep
authors.initials: N
authors.lastname: Tangri
mesh_terms: D000368:Aged; D002423:Cause of Death / Q000639:trends; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007676:Kidney Failure, Chronic / Q000401:mortality / Q000628:therapy*; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D012042:Registries; D006435:Renal Dialysis / Q000401:mortality*; D012189:Retrospective Studies; D012307:Risk Factors; D015996:Survival Rate / Q000639:trends; D006113:United Kingdom / Q000453:epidemiology