Research Article: Individual patient variability with the application of the kidney failure risk equation in advanced chronic kidney disease

Date Published: June 12, 2018

Publisher: Public Library of Science

Author(s): Christopher McCudden, Ayub Akbari, Christine A. White, Mohan Biyani, Swapnil Hiremath, Pierre Antoine Brown, Navdeep Tangri, Scott Brimble, Greg Knoll, Peter G. Blake, Manish M. Sood, Ping-Hsun Wu.

http://doi.org/10.1371/journal.pone.0198456

Abstract

The Kidney Failure Risk Equation (KFRE) predicts the need for dialysis or transplantation using age, sex, estimated glomerular filtration rate (eGFR), and urine albumin to creatinine ratio (ACR). The eGFR and ACR have known biological and analytical variability. We examined the effect of biological and analytical variability of eGFR and ACR on the 2-year KFRE predicted kidney failure probabilities using single measure and the average of repeat measures of simulated eGFR and ACR. Previously reported values for coefficient of variation (CV) for ACR and eGFR were used to calculate day to day variability. Variation was also examined with outpatient laboratory data from patients with an eGFR between 15 and 50 mL/min/1.72 m2. A web application was developed to calculate and model day to day variation in risk. The biological and analytical variability related to ACR and eGFR lead to variation in the predicted probability of kidney failure. A male patient age 50, ACR 30 mg/mmol and eGFR 25, had a day to day variation in risk of 7% (KFRE point estimate: 17%, variability range 14% to 21%). The addition of inter laboratory variation due to different instrumentation increased the variability to 9% (KFRE point estimate 17%, variability range 13% to 22%). Averaging of repeated measures of eGFR and ACR significantly decreased the variability (KFRE point estimate 17%, variability range 15% to 19%). These findings were consistent when using outpatient laboratory data which showed that most patients had a KFRE 2-year risk variability of ≤ 5% (79% of patients). Approximately 13% of patients had variability from 5–10% and 8% had variability > 10%. The mean age (SD) of this cohort was 64 (15) years, 36% were females, the mean (SD) eGFR was 32 (10) ml/min/1.73m2 and median (IQR) ACR was 22.7 (110). Biological and analytical variation intrinsic to the eGFR and ACR may lead to a substantial degree of variability that decreases with repeat measures. Use of a web application may help physicians and patients understand individual patient’s risk variability and communicate risk (https://mccudden.shinyapps.io/kfre_app/). The web application allows the user to alter age, gender, eGFR, ACR, CV (for both eGFR and ACR) as well as units of measurements for ACR (g/mol versus mg/g).

Partial Text

The growing advanced chronic kidney disease (CKD) population is a widely recognized global health issue[1]. In patients with advanced and declining kidney function, multiple interventions including modality education and vascular access planning are required, ideally prior to the development of end stage kidney disease (ESKD) [2]. However, most patients with CKD do not progress to ESKD [3]. Thus assessment of risk of ESKD is necessary for counseling of patients and adequate advanced care planning.

This was a two-part study using simulated and real patient data.

To our knowledge this is the first study simulating the day-to-day variability of KFRE-based probability due to day-to-day variation of eGFR and ACR. We have shown significant variability in KFRE risk across all models, which was greatest at lower levels of eGFR and higher levels of ACR. Addition of variability due to inter-laboratory differences further increased the KFRE variability estimates. Reductions in KFRE variability were achieved using repeat averaged measures of first morning ACR and averaged eGFR. With real patient data, the majority of patients (79%) had variability in the 2-year KFRE risk of 5% or less; conversely only 8% had variability of greater than 10%.

 

Source:

http://doi.org/10.1371/journal.pone.0198456

 

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