Predictive Model for Progression of CKD to Kidney Failure

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Clinicians may have an important new tool they can use to better predict which patients with chronic kidney disease (CKD) will progress to kidney failure.

American and Canadian researchers have come up with a model using routinely obtained laboratory tests that appears to accurately predict progression to kidney failure in patients with CKD stages 3-5.

Navdeep Tangri, MD, of Tufts Medical Center in Boston, and colleagues tested several models and found one in particular that is particularly user-friendly. The model uses age, gender, estimated glomerular filtration rate (eGFR), albuminuria, serum calcium, serum phosphate, serum bicarbonate, and serum albumin, according to a report in the Journal of the American Medical Association (2011;305:1553-1159). This model was more accurate than a simpler model that included age, gender, eGFR, and albuminuria.

Currently, CKD severity is classified by eGFR and albuminuria, but more accurate information regarding risk of progression to kidney failure may help better guide clinical decisions about testing, treatment, and referral. 

The investigators used two different CKD cohorts. The development cohort included 3,449 patients; in this group, 386 patients (11%) had kidney failure. The validation cohort included 4,942 patients; in this group 1,177 patients (24%) had kidney failure. Patients in both groups were similar in age and sex and had similar prevalence of diabetes and smoking.

External validation in multiple diverse CKD cohorts and evaluation in clinical trials are still needed, the researchers noted.  However, they write that using their single risk equation may allow different risk thresholds to be used to triage patients for decisions regarding dialysis modality education, vascular access creation, and pre-emptive transplantation.

 

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