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Predicting outcome in the idiopathic glomerulopathies
1Toronto Hospital, Ontario-Canada.
Improving accuracy in predicting outcome in the idiopathic glomerulopathies requires standard clinical and laboratory data observed over time and the application of certain basic biostatistical tests. In our initial model we examined categories of glomerular disease that progress i.e. membranous, membranoproliferative, diffuse proliferative, focal sclerosing and IgA nephropathy. We determined that a combination of severity and persistence of proteinuria above certain levels over fixed time frames plus the knowledge of any change in glomerular filtration rate during these periods resulted in slopes of creatinine clearances that were the same across this histologic spectrum. This modeling of disease was then applied in a more rigorous fashion to our patients with idiopathic membranous nephropathy (IMGN). Multivariate logistic regression analyses was used to test all other potential clinical and laboratory predictors of chronic renal failure. These additional factors did not improve our ability to predict outcome. This algorithm was subsequently validated on two independent IMGN data bases. Overall accuracy of prediction estimated within 6 months of presentation was maintained at > 85%. The role of this type of evaluation in both clinical practice and research is discussed.
Improving accuracy in predicting outcome in the idiopathic glomerulopathies requires standard clinical and laboratory data observed over time and the application of certain basic biostatistical tests. In our initial model we examined categories of glomerular disease that progress i.e. membranous, membranoproliferative, diffuse proliferative, focal sclerosing and IgA nephropathy. We determined that a combination of severity and persistence of proteinuria above certain levels over fixed time frames plus the knowledge of any change in glomerular filtration rate during these periods resulted in slopes of creatinine clearances that were the same across this histologic spectrum. This modeling of disease was then applied in a more rigorous fashion to our patients with idiopathic membranous nephropathy (IMGN). Multivariate logistic regression analyses was used to test all other potential clinical and laboratory predictors of chronic renal failure. These additional factors did not improve our ability to predict outcome. This algorithm was subsequently validated on two independent IMGN data bases. Overall accuracy of prediction estimated within 6 months of presentation was maintained at > 85%. The role of this type of evaluation in both clinical practice and research is discussed.