Utility of Urinary Biomarkers in Predicting Loss of Residual Renal Function: The balANZ Trial.
BACKGROUND
The ability of urinary biomarkers to predict residual renal function (RRF) decline in peritoneal dialysis (PD) patients has not been defined. The present study aimed to explore the utility of established biomarkers from kidney injury models for predicting loss of RRF in incident PD patients, and to evaluate the impact on RRF of using neutral-pH PD solution low in glucose degradation products.


METHODS
The study included 50 randomly selected participants from the balANZ trial who had completed 24 months of follow-up. A change in glomerular filtration rate (GFR) was used as the primary clinical outcome measure. In a mixed-effects general linear model, baseline measurements of 18 novel urinary biomarkers and albumin were used to predict GFR change. The model was further used to evaluate the impact of biocompatible PD solution on RRF, adjusted for each biomarker.


RESULTS
Baseline albuminuria was not a useful predictor of change in RRF in PD patients (p = 0.84). Only clusterin was a significant predictor of GFR decline in the whole population (p = 0.04, adjusted for baseline GFR and albuminuria). However, the relationship was no longer apparent when albuminuria was removed from the model (p = 0.31). When the effect of the administered PD solutions was examined using a model adjusted for PD solution type, baseline albuminuria, and GFR, higher baseline urinary concentrations of trefoil factor 3 (TFF3, p = 0.02), kidney injury molecule 1 (KIM-1, p = 0.04), and interferon γ-induced protein 10 (IP-10, p = 0.03) were associated with more rapid decline of RRF in patients receiving conventional PD solution compared with biocompatible PD solution.


CONCLUSIONS
Higher urinary levels of kidney injury biomarkers (TFF3, KIM-1, IP-10) at baseline predicted significantly slower RRF decline in patients receiving biocompatible PD solutions. Findings from the present investigation should help to guide future studies to validate the utility of urinary biomarkers as tools to predict RRF decline in PD patients.
Department of Renal Medicine, Princess Alexandra Hospital, Brisbane, Australia School of Medicine, University of Queensland, Brisbane, Australia Translational Research Institute, Brisbane, Australia.
Yeoungjee
Y
Cho
Department of Renal Medicine, Princess Alexandra Hospital, Brisbane, Australia School of Medicine, University of Queensland, Brisbane, Australia Translational Research Institute, Brisbane, Australia.
David W
DW
Johnson
Department of Renal Medicine, Princess Alexandra Hospital, Brisbane, Australia School of Medicine, University of Queensland, Brisbane, Australia Translational Research Institute, Brisbane, Australia.
David A
DA
Vesey
Department of Renal Medicine, Princess Alexandra Hospital, Brisbane, Australia School of Medicine, University of Queensland, Brisbane, Australia Translational Research Institute, Brisbane, Australia.
Carmel M
CM
Hawley
Fresenius Medical Care, Sydney, Australia.
Margaret
M
Clarke
Institute of Translation, Innovation, Methodology and Engagement, Cardiff University School of Medicine, Cardiff, UK.
Nicholas
N
Topley
D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000652:urine; D051152:Clusterin / Q000652:urine; D015314:Dialysis Solutions; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007676:Kidney Failure, Chronic / Q000175:diagnosis / Q000628:therapy* / Q000652:urine*; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D010530:Peritoneal Dialysis; D011237:Predictive Value of Tests
D015415:Biomarkers; D051152:Clusterin; D015314:Dialysis Solutions
Biocompatibility; biomarkers; glucose degradation products; kidney injury; residual renal function