Abstract: TH-PO897
Estimating Time to Kidney Failure: Comparison of KFRE and eGFR Thresholds
Session Information
- CKD: Epidemiology, Risk Factors, Prevention - I
November 03, 2022 | Location: Exhibit Hall, Orange County Convention Center‚ West Building
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2201 CKD (Non-Dialysis): Epidemiology‚ Risk Factors‚ and Prevention
Authors
- Chu, Chi D., University of California San Francisco, San Francisco, California, United States
- Mcculloch, Charles E., University of California San Francisco, San Francisco, California, United States
- Hsu, Raymond K., University of California San Francisco, San Francisco, California, United States
- Powe, Neil R., University of California San Francisco, San Francisco, California, United States
- Bieber, Brian, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
- Robinson, Bruce M., Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
- Pecoits-Filho, Roberto, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
- Raina, Rupesh, Akron Children's Hospital, Akron, Ohio, United States
- Tuot, Delphine S., University of California San Francisco, San Francisco, California, United States
Background
The Kidney Failure Risk Equation (KFRE) is a widely validated model for predicting the risk of ESKD at 2 years among persons with CKD. We examined correspondences between KFRE-predicted risk and time to ESKD and compared them to eGFR thresholds.
Methods
In the CKDopps cohort study of patients with CKD G3-G5 recruited from 34 US nephrology practices 2013-2021, the KFRE-predicted 2-year risk of ESKD was computed using age, sex, UACR, and eGFR (2021 CKD-EPI equation without race) and analyzed. For persons missing UACR, we substituted UPCR or urinalysis protein as available, converting to UACR using validated equations. Each participant could contribute multiple risk periods based on updated KFRE predictions calculated at follow up visits. We used accelerated failure time (Weibull) models to estimate median, 25th, and 75th percentile times to reaching ESKD starting from KFRE values of 10%, 20%, 40% and from eGFR values of 30, 20, and 15 ml/min/1.73m2. We additionally examined time to ESKD in subgroups by age, sex, race, diabetes status, and albuminuria. Robust standard errors were used to account for clustering by participant.
Results
1,634 participants (mean age 68±13 years; 48.7% female; mean eGFR 29±12 ml/min/1.73m2; median UACR 104 [IQR 25, 803] mg/g) were included, contributing 9,886 risk periods. Over a median follow up of 1.6 years (IQR 1.0, 2.5), 266 participants developed ESKD and 178 died. Median time to ESKD was highly variable across subgroups from eGFR thresholds of 30 and 20 ml/min/1.73m2 (Figure) and was shorter for Black (versus non-Black), diabetic (versus non-diabetic), younger age, and higher albuminuria subgroups. There was less subgroup variability from an eGFR of 15 ml/min/1.73m2 and from KFRE thresholds.
Conclusion
Compared with eGFR, KFRE thresholds demonstrated less variability across subgroups in time to ESKD and may be advantageous for informing clinical decisions about kidney replacement therapy.
Funding
- Private Foundation Support