Predictive value of spot versus 24-hour measures of proteinuria for death, end-stage kidney disease or chronic kidney disease progression

Abstract

Background: Proteinuria is well recognised as a marker of chronic kidney disease (CKD), as a risk factor for progression of CKD among those with known CKD, and as a risk factor for cardiovascular events and death among both the general and CKD populations. Which measure of proteinuria is most predictive of renal events remains uncertain.

Methods: We conducted a prospective study with 144 proteinuric CKD and kidney transplant recipients attending an outpatient clinic of a tertiary care hospital in Australia. We concurrently collected morning spot urine protein-to-creatinine ratio (UPCR), albumin-to-creatinine ratio (UACR) and 24-h urinary protein excretion (24-UPE) from each participant at baseline. The primary outcome was a composite of death, ESKD or > 30% decline in eGFR over 5-years. Secondary outcomes were each component of the composite outcome. For each proteinuria measure, we performed a Cox Proportional Hazards model and calculated the Harrell's C-statistic and Akaike's Information Criterion (AIC).

Results: After a mean follow-up of 5 years (range 4.4-6), 85 (59%) patients met the primary composite outcome including 23 deaths (16%). The multivariable analysis showed strong evidence of an association between each log-transformed proteinuria measurement and the primary composite outcome. [Log-UPCR 1.31 (95% CI 1.18-1.63), log-UACR 1.27 (1.11-1.45) and log-24-UPE 1.43 (1.20-1.71)]. The C-Statistic were similar for all three measures of proteinuria [UPCR: 0.74 (95% CI: 0.69-0.80), UACR: 0.75 (0.69-0.81), 24-UPE: 0.75 (0.69-0.81)] as were the models' AIC (671, 668 and 665 respectively). For secondary outcomes, no proteinuria measure was significantly associated with death alone ([log-UPCR = 1.18 (0.96-1.84), log-UACR = 1.19 (1.00-1.55), log-24-UPE = 1.19 (0.83-1.71)], whilst UACR and 24-UPE demonstrated marginally better association with ESKD and > 30% decline in eGFR respectively. [For ESKD, adj log-UACR HR = 1.33 (1.07-1.66). For > 30% decline in eGFR, log-24-UPE adj HR = 1.54 (1.13-2.09)].

Conclusion: In patients with stable, non-nephrotic CKD, all three measures of proteinuria were similarly predictive of hard clinical endpoints, defined as a composite of death, ESKD and > 30% decline in eGFR. However, which measure best predicted the outcomes individually is less certain.

Keywords: Albumin-to-creatinine ratio; Albuminuria; Chronic kidney disease; Protein-to-creatinine ratio; Proteinuria; Renal outcomes.

Fig. 1

Study participant and flow

Fig. 2

Kaplan-Meier survival curves for the primary outcome for a hypothetical patient as measured by (a) albumin-to-creatinine ratio and (b) 24-h urine protein excretion. Note: survival probability = survival free from death, end-stage kidney disease or > 30% decline in estimated glomerular filtrate rate ACR = albumin-to-creatinine ratio, DM = diabetes mellitus, HTN = hypertension, prot = protein

Fig. 3

Forest plot showing the adjusted hazard ratio and 95% confidence interval of the association between proteinuria measures and the primary outcome. The association between the three baseline measures of proteinuria and the primary composite outcome shown for all patients, CKD (non-transplant) patients and transplant patients. The multivariable model for “all patients” is adjusted for baseline age, eGFR, hypertension and diabetes mellitus. The model stratified by transplant status includes age, eGFR, hypertension, diabetes mellitus and the interaction term between transplant status and the measure of proteinuria. The p- value for the interaction term is shown. The diamonds represent the HR and the horizontal bars the 95% CI. UPCR = urine protein-to-creatinine ratio, Pts = patients, UACR = urine albumin-to- creatinine ratio, 24 h = 24-h protein excretion, HR = Hazard ratio, CI = confidence intervals, eGFR = estimated glomerular filtration rate