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Predicting renal replacement therapy and mortality in CKD
Eric S Johnson1, Micah L Thorp, Xiuhai Yang
1Center for Health Research, Kaiser Permanente Northwest, Portland, OR 97227, USA.
Insights
This study found that while age, sex, eGFR, diabetes, hypertension, and anemia effectively predict kidney replacement therapy (RRT) progression, hypertension and age have opposite effects on mortality. Separate risk scores are needed for RRT and mortality prediction.
Area of Science:
- Nephrology
- Epidemiology
- Biostatistics
Background:
- Prognostic risk scores aid clinicians in managing patients with chronic kidney disease (CKD).
- Identifying predictors of CKD progression to renal replacement therapy (RRT) is crucial for patient management.
- Understanding factors influencing mortality in CKD patients is essential.
Purpose of the Study:
- To identify patient characteristics that predict the rate of progression to RRT.
- To evaluate how these characteristics predict mortality.
- To assess the prediction of a composite endpoint of RRT and mortality.
Main Methods:
- Retrospective cohort study design.
- Inclusion of 6,541 members from Kaiser Permanente Northwest with CKD (eGFR < 60 mL/min/1.73 m(2)).
- Analysis using Cox regression to calculate adjusted hazard ratios and concordance statistics.
Main Results:
- Six characteristics (age, sex, eGFR, diabetes, hypertension, anemia) effectively predicted RRT progression (c-statistic = 0.91).
- Hypertension and age predicted mortality and the composite endpoint in the opposite direction.
- Prediction for mortality (c-statistic = 0.70) and the composite endpoint (c-statistic = 0.71) was less effective.
Conclusions:
- A distinct risk score is necessary for predicting RRT progression.
- A separate risk score is recommended for the composite endpoint, prioritizing mortality predictors.
- Missing data and lack of standardized measurement protocols limited the evaluation of certain risk factors.
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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