Predicting renal replacement therapy and mortality in CKD

Eric S Johnson, Micah L Thorp, Xiuhai Yang, Olivier L Charansonney, David H Smith
American Journal of Kidney Diseases 2007, 50 (4): 559-65

BACKGROUND: Prognostic risk scores can help clinicians intervene on higher risk patients and counsel them. Our objective is to identify characteristics that predict the rate of progression to renal replacement therapy (RRT) and evaluate how those characteristics predict mortality and a composite end point (RRT and mortality).

STUDY DESIGN: Retrospective cohort study.

SETTING & PARTICIPANTS: We conducted the study at Kaiser Permanente Northwest, a health maintenance organization. We followed up members with an estimated glomerular filtration rate (eGFR) that indicated chronic kidney disease (2 eGFRs < 60 mL/min/1.73 m(2) [<1.0 mL/s/1.73 m(2)] at least 90 days apart).

PREDICTORS: We measured baseline clinical characteristics between January 1997 and June 2000 by using electronic medical records and patients' histories of hospitalization.

OUTCOMES & MEASUREMENTS: We calculated adjusted hazard ratios and concordance statistics for progression to RRT, mortality, and the composite by using Cox regression.

RESULTS: Patients (n = 6,541) were followed up for up to 5 years. We observed 1.6 progressions to RRT/100 person-years and 11.4 deaths/100 person-years. The 6 characteristics of age, sex, eGFR, diabetes, hypertension, and anemia predicted RRT effectively (c statistic, 0.91). However, hypertension and age predicted in the opposite direction for mortality and its composite end point. The c statistic decreased: mortality (0.70), mortality and RRT (0.71).

LIMITATIONS: Characteristics were measured without a protocol; extensive missing data prevented the evaluation of known risk factors (eg, proteinuria).

CONCLUSIONS: Predicting RRT effectively requires a separate risk score. Predicting the composite end point would favor characteristics that predict mortality because it is 7 times as common as RRT.


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