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  • Title: Validation of the international IgA nephropathy prediction tool in a French cohort beyond 10 years after diagnosis.
    Author: Bon G, Jullien P, Masson I, Sauron C, Dinic M, Claisse G, Pelaez A, Thibaudin D, Mohey H, Alamartine E, Mariat C, Maillard N.
    Journal: Nephrol Dial Transplant; 2023 Sep 29; 38(10):2257-2265. PubMed ID: 37316441.
    Abstract:
    INTRODUCTION: The International IgA Nephropathy Network developed a tool (IINN-PT) for predicting the risk of end-stage renal disease (ESRD) or a 50% decline in the estimated glomerular filtration rate (eGFR). We aimed to validate this tool in a French cohort with longer follow-up than previously published validation studies. METHODS: The predicted survival of patients with biopsy-proven immunoglobulin A nephropathy (IgAN) from the Saint Etienne University Hospital cohort was computed with IINN-PT models with or without ethnicity. The primary outcome was the occurrence of either ESRD or a 50% decline in eGFR. The models' performances were evaluated through c-statistics, discrimination and calibration analysis. RESULTS: There were 473 patients with biopsy-proven IgAN, with a median follow-up of 12.4 years. Models with and without ethnicity showed areas under the curve (95% confidence interval) of 0.817 (0.765; 0.869) and 0.833 (0.791; 0.875) and R2D of 0.28 and 0.29, respectively, and an excellent discrimination of groups of increasing predicted risk (P < .001). The calibration analysis was good for both models up to 15 years after diagnosis. The model without ethnicity exhibited a mathematical issue of survival function after 15 years. DISCUSSION: The IINN-PT provided good performances even after 10 years post-biopsy as showed by our study based on a cohort with a longer follow-up than previous cohorts (12.4 versus <6 years). The model without ethnicity exhibited better performances up to 15 years but became aberrant beyond this point due to a mathematical issue affecting the survival function. Our study sheds light on the usefulness of integrating ethnicity as a covariable for prediction of IgAN course.
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