Validation of the International IgA Nephropathy Prediction Tool in the Greek Registry of IgA Nephropathy

BackgroundImmunoglobulin A nephropathy (IgAN) is among the commonest glomerulonephritides in Greece and an important cause of end-stage kidney disease (ESKD) with an insidious chronic course. Thus, the recently published International IgAN prediction tool could potentially provide valuable risk stratification and guide the appropriate treatment module. This study aimed to externally validate this prediction tool using a patient cohort from the IgAN registry of the Greek Society of Nephrology.MethodsWe validated the predictive performance of the two full models (with or without race) derived from the International IgAN Prediction Tool study in the Greek Society of Nephrology registry of patients with IgAN using external validation of survival prediction models (Royston and Altman). The discrimination and calibration of the models were tested using the C-statistics and stratified analysis, coefficient of determination (RD2) for model fit, and the regression coefficient of the linear predictor (βPI), respectively.ResultsThe study included 264 patients with a median age of 39 (30–51) years where 65.2% are men. All patients were of Caucasian origin. The 5-year risk of the primary outcome (50% reduction in estimated glomerular filtration rate or ESKD) was 8%. The RD2 for the full models with and without race when applied to our cohort was 39 and 35%, respectively, and both were higher than the reported RD2 for the models applied to the original validation cohorts (26.3, 25.3, and 35.3%, respectively). Harrel's C statistic for the full model with race was 0.71, and for the model without race was 0.70. Renal survival curves in the subgroups (<16th, ~16 to <50th, ~50 to <84th, and >84th percentiles of linear predictor) showed adequate separation. However, the calibration proved not to be acceptable for both the models, and the risk probability was overestimated by the model.ConclusionsThe two full models with or without race were shown to accurately distinguish the highest and higher risk patients from patients with low and intermediate risk for disease progression in the Greek registry of IgAN..

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:9

Enthalten in:

Frontiers in Medicine - 9(2022)

Sprache:

Englisch

Beteiligte Personen:

Marios Papasotiriou [VerfasserIn]
Maria Stangou [VerfasserIn]
Dimitris Chlorogiannis [VerfasserIn]
Smaragdi Marinaki [VerfasserIn]
Dimitrios Xydakis [VerfasserIn]
Erasmia Sampani [VerfasserIn]
Georgios Lioulios [VerfasserIn]
Eleni Kapsia [VerfasserIn]
Synodi Zerbala [VerfasserIn]
Maria Koukoulaki [VerfasserIn]
Georgios Moustakas [VerfasserIn]
Stavros Fokas [VerfasserIn]
Evangelia Dounousi [VerfasserIn]
Anila Duni [VerfasserIn]
Antonia Papadaki [VerfasserIn]
Nikolaos Damianakis [VerfasserIn]
Dimitra Bacharaki [VerfasserIn]
Kostas Stylianou [VerfasserIn]
Hariklia Gakiopoulou [VerfasserIn]
George Liapis [VerfasserIn]
Georgios Sakellaropoulos [VerfasserIn]
Evangelos Papachristou [VerfasserIn]
Ioannis Boletis [VerfasserIn]
Aikaterini Papagianni [VerfasserIn]
Dimitrios S. Goumenos [VerfasserIn]

Links:

doi.org [kostenfrei]
doaj.org [kostenfrei]
www.frontiersin.org [kostenfrei]
Journal toc [kostenfrei]

Themen:

ACE inhibitors
Chronic kidney disease
IgAN disease progression
IgAN prediction tool
Immunosuppression
Medicine (General)

doi:

10.3389/fmed.2022.778464

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

DOAJ045528527