title: Predictive power of sequential measures of albuminuria for progression to ESRD or death in Pima Indians with type 2 diabetes.
abstract: BACKGROUND
  To determine whether historic albuminuria measurements provide additional predictive value for diabetic end-stage renal disease (ESRD) and natural mortality over the most recent measurement, ie, whether "regression" from high albuminuria has a different prognosis than stability at the lower level.
  
  
  METHODS
  Observational longitudinal study.
  
  
  METHODS
  Pima Indians 15 years or older with type 2 diabetes and at least 2 consecutive measurements of urinary albumin-creatinine ratio (ACR) within 6 years.
  
  
  METHODS
  Sequential measurements of urinary ACR.
  
  
  METHODS
  Proportional hazards analyses were used to estimate the risk of ESRD and natural death associated with the first and second ACR measurement. The ability of these highly correlated variables to predict outcome was compared with receiver operating characteristic curves calculated by means of the generalized c statistic.
  
  
  RESULTS
  In 983 subjects, 136 developed ESRD and 180 died of natural causes during a maximum follow-up of 12.6 years. Each doubling in the second ACR was associated with a 1.71-fold greater incidence of ESRD (95% confidence interval, 1.54 to 1.89) and 1.16-fold greater natural mortality (95% confidence interval, 1.07 to 1.27) adjusted for age, sex, diabetes duration, and antihypertensive medication. The addition of the first ACR measurement to the model did not add to the predictive value for ESRD or mortality. In pairwise comparisons of c statistics, the second ACR was a significantly better predictor of ESRD than the first ACR.
  
  
  CONCLUSIONS
  The predictive value of ACR measurements is decreased to the extent that its precision is based on a single measure.
  
  
  CONCLUSIONS
  The predictive power of the latest ACR for ESRD and natural mortality in patients with diabetes is not enhanced by knowledge of the preceding ACR. Therefore, ACR changes over time, ie, regression or progression, add minimal predictive value beyond the latest measurement in the series.
authors.affiliation: Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ 85014-4972, USA. mpavkov@cdc.gov
authors.forename: Meda E
authors.initials: ME
authors.lastname: Pavkov
authors.forename: William C
authors.initials: WC
authors.lastname: Knowler
authors.forename: Robert L
authors.initials: RL
authors.lastname: Hanson
authors.forename: Peter H
authors.initials: PH
authors.lastname: Bennett
authors.forename: Robert G
authors.initials: RG
authors.lastname: Nelson
mesh_terms: D000328:Adult; D000419:Albuminuria / Q000175:diagnosis*; D003924:Diabetes Mellitus, Type 2 / Q000150:complications* / Q000208:ethnology / Q000401:mortality; D003928:Diabetic Nephropathies / Q000209:etiology / Q000503:physiopathology*; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007198:Indians, North American; D007676:Kidney Failure, Chronic / Q000209:etiology / Q000503:physiopathology*; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests