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

Επιστημονική δημοσίευση - Άρθρο Περιοδικού uoadl:3034576 54 Αναγνώσεις

Μονάδα:
Ερευνητικό υλικό ΕΚΠΑ
Τίτλος:
Validation of the International IgA Nephropathy Prediction Tool in the
Greek Registry of IgA Nephropathy
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
Background: Immunoglobulin 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.& nbsp;Methods: We 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 (beta(PI)),
respectively.& nbsp;Results: The 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, similar to 16 to < 50th,
similar to 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.& nbsp;Conclusions: The 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.
Έτος δημοσίευσης:
2022
Συγγραφείς:
Papasotiriou, Marios
Stangou, Maria
Chlorogiannis, Dimitris and
Marinaki, Smaragdi
Xydakis, Dimitrios
Sampani, Erasmia and
Lioulios, Georgios
Kapsia, Eleni
Zerbala, Synodi
Koukoulaki,
Maria
Moustakas, Georgios
Fokas, Stavros
Dounousi, Evangelia
and Duni, Anila
Papadaki, Antonia
Damianakis, Nikolaos and
Bacharaki, Dimitra
Stylianou, Kostas
Gakiopoulou, Hariklia and
Liapis, George
Sakellaropoulos, Georgios
Papachristou, Evangelos
and Boletis, Ioannis
Papagianni, Aikaterini
Goumenos, Dimitrios
S.
Περιοδικό:
Frontiers in Cardiovascular Medicine
Εκδότης:
Frontiers Media SA
Τόμος:
9
Λέξεις-κλειδιά:
IgAN prediction tool; IgAN disease progression; chronic kidney disease;
immunosuppression; ACE inhibitors
Επίσημο URL (Εκδότης):
DOI:
10.3389/fmed.2022.778464
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