American Journal of Kidney Diseases
Volume 52, Issue 4 , Pages 653-660, October 2008

Predicting the Risk of Dialysis and Transplant Among Patients With CKD: A Retrospective Cohort Study

  • Eric S. Johnson, PhD

      Affiliations

    • Center for Health Research, Kaiser Permanente Northwest, Portland, OR
  • ,
  • Micah L. Thorp, DO, MPH

      Affiliations

    • Department of Nephrology, Kaiser Permanente Northwest, Portland, OR
  • ,
  • Robert W. Platt, PhD

      Affiliations

    • McGill University Health Centre Research Institute, Montreal, Quebec, Canada
  • ,
  • David H. Smith, RPh, PhD

      Affiliations

    • Center for Health Research, Kaiser Permanente Northwest, Portland, OR
    • Corresponding Author InformationAddress correspondence to David H. Smith, RPh, PhD, Center for Health Research, Kaiser Permanente Northwest, 3800 North Interstate Ave, Portland, OR 97227

Received 13 September 2007; accepted 17 April 2008. published online 01 July 2008.

Background

Providers need a reliable way to identify patients with chronic kidney disease (CKD) at the highest risk of progression to end-stage renal disease so they can intervene to slow progression and refer patients to nephrology for comanagement. We developed a risk score to predict the 5-year risk of renal replacement therapy (RRT) in patients with stage 3 or 4 CKD.

Study Design

Retrospective cohort study.

Setting & Participants

Participants were members of a health maintenance organization and met Kidney Disease Outcomes Quality Initiative criteria for stage 3 or 4 CKD during 1999 or 2000: two estimated glomerular filtration rate values of 15 to 59 mL/min/1.73 m2.

Predictor

Characteristics collected during routine clinical practice.

Outcomes & Measurements

We ascertained the onset of RRT (dialysis or kidney transplantation) using the health maintenance organization databases. Cox regression predicted patient risk of RRT and generated a risk scoring system.

Results

9,782 patients experienced a 3.3% five-year progression to RRT (95% confidence interval, 2.9 to 3.7). Using 6 characteristics (age, sex, estimated glomerular filtration rate, diabetes, anemia, and hypertension), the risk score discriminated the highest risk patients effectively: 19.0% of patients in the highest risk quintile experienced progression, and 0.2% of patients in the lowest risk quintile experienced progression. The c statistic also showed effective discrimination: 0.89 on a scale of 0.5 to 1.0. Predicted and observed risks agreed within 1.0%—effective calibration. We present a range of predicted risk cutoff values from 1% to 20% and their test properties for decision makers' consideration.

Limitations

Characteristics were measured without a protocol.

Conclusions

The risk score can help providers identify patients with CKD at the highest risk of progression to improve referral to nephrology for comanagement. A separate risk score for mortality also is needed.

Index Words: Chronic kidney disease, mortality, end-stage renal disease, dialysis, kidney transplant, cohort study, natural history study, survival analysis, managed care, health maintenance organization

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 Originally published online as doi:10.1053/j.ajkd.2008.04.026 on July 1, 2008.

PII: S0272-6386(08)00886-X

doi:10.1053/j.ajkd.2008.04.026

Refers to article:

  • Predicting Outcomes in CKD

    Tobias Kurth, Robert J. Glynn
    American Journal of Kidney Diseases October 2008 (Vol. 52, Issue 4, Pages 635-637)

American Journal of Kidney Diseases
Volume 52, Issue 4 , Pages 653-660, October 2008