JAMA Internal Medicine
Sean J. Barbour, Rosanna Coppo, Hong Zhang, Zhi-Hong Liu, Keiichi Matsuzaki, Ritsuko Katafuchi, Lee Er, Gabriela Espino-Hernandez, S. Joseph Kim, Heather N. Reich, John Feehally, Daniel C. Cattran
Summary by Aiza Waheed, UBC Nephrology Fellow
IgA nephropathy is the most common glomerulonephritis in the world and the rate of progression to end stage renal disease is highly variable and dependent on a number of variables including age, race, sex, proteinuria, blood pressure, histologic scores, eGFR and medications (RAS inhibition, immunosuppression). To date, few tools have existed to accurately predict disease progression in this patient population. In this paper, Dr. Barbour and colleagues derive and externally validate a prediction model for disease progression in IgA nephropathy using international, multi-ethnic cohorts of patients with IgA nephropathy. Two models are presented and validated using the aforementioned variables, one including the race variable and one without race to allow application of the model to in various ethnic groups.
This prediction model is available through QxMD mobile-app and also at the following website: https://qxmd.com/calculate-by-qxmd.
Evaluating a new international risk prediction tool in IgA Nephropathy JAMA Internal Medicine (PDF)