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Risk Stratification to Predict Renal Survival in Anti-Glomerular Basement Membrane Disease
Lauren Floyd1,2, Sebastian Bate3,4, Abdul Hadi Kafagi1
1Division of Cardiovascular Sciences, School of Medical Sciences, University of Manchester, Manchester, United Kingdom.
The renal risk score for ANCA-associated vasculitis can predict outcomes in anti-glomerular basement membrane disease. Stratifying patients by need for renal replacement therapy and normal glomeruli percentage improves prognostication.
Area of Science:
- Nephrology
- Immunology
- Glomerular Diseases
Background:
- Anti-glomerular basement membrane (GBM) disease often presents as rapidly progressive glomerulonephritis, frequently leading to end-stage kidney disease (ESKD).
- Limited tools exist for prognostication and management of this rare condition.
Purpose of the Study:
- To investigate clinical and histologic parameters predicting kidney outcomes in anti-GBM disease.
- To explore the transferability of the renal risk score (RRS) from ANCA-associated vasculitis to anti-GBM disease.
- To identify patients who may benefit from rescue immunosuppressive therapy.
Main Methods:
- Retrospective, multicenter, international cohort study of 174 patients with anti-GBM disease.
- Analysis of clinical and histologic parameters, including the percentage of normal glomeruli and need for renal replacement therapy (RRT) at diagnosis.
- Application and validation of the RRS concept.
Main Results:
- The RRS strongly predicted ESKD, with 36-month renal survival rates of 100% (low-risk), 62.4% (moderate-risk), and 20.7% (high-risk).
- Need for RRT and percentage of normal glomeruli were independent predictors of ESKD.
- A model incorporating RRT and normal glomeruli percentage achieved superior discrimination for renal survival, with distinct outcomes across four risk groups.
Conclusions:
- The RRS concept is transferable and applicable to anti-GBM disease.
- Stratification by RRT status and renal histology (specifically normal glomeruli percentage) significantly improves outcome prediction.
- This stratification approach can aid in the clinical management of anti-GBM disease.
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