Risk Stratification to Predict Renal Survival in Anti-GBM Disease

Anti-glomerular basement membrane (GBM) disease is a rare, aggressive vasculitis with no validated prediction tools to assist its management. We investigated a retrospective multicenter international cohort with the aim to transfer the Renal Risk Score (RRS) and to identify patients that benefit from rescue immunosuppressive therapy. Of a total 191 patients, 174 patients were included in the final analysis (57% female, median age 59 years). Using Cox and Kaplan-Meier methods, the RRS was found to be a strong and effective predictor for end stage kidney disease (ESKD) with a model concordance of C=0.760. The 36-month renal survival was 100%, 62.4%, and 20.7% in the low-, moderate-, and high-risk groups, respectively (P0.001). The need for renal replacement therapy (RRT) at diagnosis and the percentage of normal glomeruli in the biopsy were independent predictors of ESKD (P0.001, P0.001). Considering the 129 patients initially requiring RRT, the best predictor for renal recovery was the percentage of normal glomeruli (C=0.622; P0.001), a split either side of 10% providing good stratification. A model with the predictors RRT and normal glomeruli (N) achieved superior discrimination (C=0.840, P0.001). Dividing patients into four risk groups led to a 36-month renal survival of 96.4% (no RRT, N≥10%), 74.0% (no RRT, N10%), 42.3% (RRT, N≥10%) and 14.1% (RRT, N10%), respectively. In summary, we demonstrate that the RRS concept is transferrable to anti-GBM disease. Stratifying patients according to the need for RRT at diagnosis and renal histology improves prediction, highlighting the importance of normal glomeruli. Here, we propose a stratification to assist in the management of anti-GBM disease.