#2710 The importance of monitoring creatinine, hematuria, and proteinuria in relation to kidney outcomes in patients with ANCA-associated vasculitis

Abstract

Abstract Background and Aims Patients with ANCA-associated vasculitis (AAV) often a have kidney involvement and it has been shown that a decreased glomerular filtration rate at entry is associated with a worse outcome both for patient and kidney survival. However, some patients present with a low kidney function at entry, but recover during treatment. Thus, it may be interesting to see if the kidney function after starting treatment is more accurate predicting outcome than the one at entry. The aim of our study was to determine the prognostic significance of proteinuria, hematuria and serum creatinine monitoring in patients with AAV Method The dataset included 848 patients with newly diagnosed AAV who participated in 7 RCTs (1995-2012), and median follow-up time of the entire cohort was 8 years (IQR: 2.9-13.6). Creatinine, hematuria, and proteinuria was recorded at baseline, 3, 6, 9, 12, and 18 months after randomization. Kidney outcome was defined as permanent dialysis dependency during follow-up or kidney transplantation. Receiver operating characteristic curves (ROC) were calculated and screening performance of cut-off scores was evaluated using the Youden Index. A multivariate Cox regression model was performed to examine the factors associated with the kidney outcome. Results Median baseline Creatinine was 176 µmol/L (IQR: 97-388.5), 114 µmol/L (IQR: 88-171) at 3 months, 110 µmol/L (IQR: 89-160) at 6 months, 110 µmol/L (IQR: 89-155) at 12 months, and 102 µmol/L (IQR: 84-132.6) at 18 months. Within 12 months, the AUC of Creatinine was the highest at 0.87 (95% CI: 0.79-0.95; SE: 0.05; p-value: 0.04) to predict kidney outcome. For the cut-off point of 135 µmol/L, 12-month-Creatinine achieved a sensitivity of 83% and specificity of 76% (LR+: 3.35, LR-: 0.23). The ROC curves for hematuria, showed that the highest AUC was found at 9 months (AUC: 0.71; SE: 0.04; 95% CI: 0.64-0.78; p = 0.032) (Fig. 1). Examination of the ROC curve of proteinuria > 0.5/24 h, revealed that the highest AUC corresponded to the baseline determination (AUC: 0.64; SE: 0.08; 95% CI: 0.48-0.80), but there was no statistically significant difference observed among the AUC values of proteinuria across the monitored periods. In the multivariable Cox regression model, MPA diagnosis, creatinine at 12 months, and age > 65 years old were independent prognostic factors for the kidney outcome. The model including Creatinine at 12 months was more robust than the model including baseline Creatinine (Harrell's C: 0.84 and 0.76, respectively) Conclusion The best diagnostic accuracy for ESKD in ROC curves was shown by serum creatinine at 12 months (AUC: 0.87; SE: 0.05; 95% CI 0.79-0.95; p-value: 0.04). Hematuria was a predictor of the kidney outcome of moderate quality (AUC 0.71; SE 0.04; 95% CI: 0.64-0.78), while proteinuria > 0. 5 g/24 h had a modest and non-significant AUC (AUC 0.64; SE 0.08; 95% CI 0.48-0.80). Serum creatinine at 12 months was found to be an independent prognostic factor for kidney outcome, while haematuria and albuminuria during follow up within the first 18 months did not seem to add any impact on outcome. Reevaluation of renal prognosis at 12 months might be useful to reassess treatment in patients with AAV. Taken together, these findings suggest than incorporating biomarker monitoring into clinical-analytical predictive models can provide a more nuanced and accurate method for predicting renal outcomes as the disease progresses.