title: Development and validation of a model to predict 5-year risk of death without ESRD among older adults with CKD.
abstract: OBJECTIVE
  CKD is associated with mortality. Accurate prediction tools for mortality may guide clinical decision-making, particularly among elderly persons with CKD.
  
  
  METHODS
  A prediction equation was developed for 5-year risk of mortality among participants with CKD in the Cardiovascular Health Study. Sixteen candidate predictor variables were explored, which included demographics, physical examination measures, comorbidity, medication use, and kidney function measures (eGFR calculated from serum creatinine and the CKD Epidemiology Collaboration equation and the urine albumin-to-creatinine ratio). Models were developed using Cox regression and evaluated using c statistics. A final parsimonious model was externally validated in an independent cohort of community-living elders with CKD in the Health, Aging, and Body Composition Study.
  
  
  RESULTS
  The development cohort included 828 participants who had a mean age of 80 (±5.6) years and an eGFR of 47 (±11) ml/min per 1.73 m(2), and median albumin-to-creatinine ratio of 13 (interquartile range 6-51) mg/g. The validation cohort included 789 participants who had a mean age of 74 (±2.8) years and an eGFR of 50 (±9) ml/min per 1.73 m(2), and median albumin-to-creatinine ratio of 13 (interquartile range 6-42) mg/g. The final model for 5-year mortality risk included age, sex, race, eGFR, urine albumin-to-creatinine ratio, smoking, diabetes mellitus, and history of heart failure and stroke (c statistic=0.72; 95% confidence interval, 0.68 to 0.74). When a point-based system was assigned for each of nine variables in the equation, the estimated risk of death within 5 years ranged from 3.8% among participants with the lowest scores to 83.6% among participants with nine points. The model performed fair in external validation (c statistic=0.69; 95% confidence interval, 0.64 to 0.74).
  
  
  CONCLUSIONS
  A simple prediction tool using nine readily available clinical variables can assist in predicting 5-year mortality risk in elderly patients with CKD, which may be useful in counseling patients and guiding clinical decision making.
authors.affiliation: Kidney Research Institute, Division of Nephrology, University of Washington, Seattle, Washington; nbansal@nephrology.washington.edu.
authors.forename: Nisha
authors.initials: N
authors.lastname: Bansal
authors.affiliation: Kidney Research Institute, Division of Nephrology, University of Washington, Seattle, Washington;
authors.forename: Ronit
authors.initials: R
authors.lastname: Katz
authors.affiliation: Kidney Research Institute, Division of Nephrology, University of Washington, Seattle, Washington;
authors.forename: Ian H
authors.initials: IH
authors.lastname: De Boer
authors.affiliation: Division of Nephrology, University of California, San Francisco, California;
authors.forename: Carmen A
authors.initials: CA
authors.lastname: Peralta
authors.affiliation: Division of Nephrology, University of Pittsburgh, Pittsburgh, Pennsylvania;
authors.forename: Linda F
authors.initials: LF
authors.lastname: Fried
authors.affiliation: New York Academy of Medicine New York, New York;
authors.forename: David S
authors.initials: DS
authors.lastname: Siscovick
authors.affiliation: Division of Nephrology, University of California, San Diego, California;
authors.forename: Dena E
authors.initials: DE
authors.lastname: Rifkin
authors.affiliation: Department of Medicine, University of California, Davis, Sacramento, California;
authors.forename: Calvin
authors.initials: C
authors.lastname: Hirsch
authors.affiliation: San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California;
authors.forename: Steven R
authors.initials: SR
authors.lastname: Cummings
authors.affiliation: National Institute on Aging;
authors.forename: Tamara B
authors.initials: TB
authors.lastname: Harris
authors.affiliation: Sticht Center on Aging and Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina; and.
authors.forename: Stephen B
authors.initials: SB
authors.lastname: Kritchevsky
authors.affiliation: Division of Nephrology, Tufts Medical Center, Boston, Massachusetts.
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Sarnak
authors.affiliation: Division of Nephrology, University of California, San Francisco, California;
authors.forename: Michael G
authors.initials: MG
authors.lastname: Shlipak
authors.affiliation: New York Academy of Medicine New York, New York;
authors.forename: Joachim H
authors.initials: JH
authors.lastname: Ix
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000419:Albuminuria / Q000652:urine; D003404:Creatinine / Q000652:urine; D003920:Diabetes Mellitus / Q000453:epidemiology; D005260:Female; D005919:Glomerular Filtration Rate; D006333:Heart Failure / Q000453:epidemiology; D006801:Humans; D008297:Male; D016016:Proportional Hazards Models; D044469:Racial Groups; D012044:Regression Analysis; D051436:Renal Insufficiency, Chronic / Q000401:mortality*; D012307:Risk Factors; D012737:Sex Factors; D012907:Smoking / Q000453:epidemiology; D020521:Stroke / Q000453:epidemiology
chemical_list: D003404:Creatinine
keywords: CKD; geriatric nephrology; mortality