Περίληψη:
ImportanceAlthough IgA nephropathy (IgAN) is the most common
glomerulonephritis in the world, there is no validated tool to predict
disease progression. This limits patient-specific risk stratification
and treatment decisions, clinical trial recruitment, and biomarker
validation. ObjectiveTo derive and externally validate a prediction
model for disease progression in IgAN that can be applied at the time of
kidney biopsy in multiple ethnic groups worldwide. Design, Setting, and
ParticipantsWe derived and externally validated a prediction model using
clinical and histologic risk factors that are readily available in
clinical practice. Large, multi-ethnic cohorts of adults with
biopsy-proven IgAN were included from Europe, North America, China, and
Japan. Main Outcomes and MeasuresCox proportional hazards models were
used to analyze the risk of a 50% decline in estimated glomerular
filtration rate (eGFR) or end-stage kidney disease, and were evaluated
using the R-D(2) measure, Akaike information criterion (AIC), C
statistic, continuous net reclassification improvement (NRI), integrated
discrimination improvement (IDI), and calibration plots. ResultsThe
study included 3927 patients; mean age, 35.4 (interquartile range,
28.0-45.4) years; and 2173 (55.3%) were men. The following prediction
models were created in a derivation cohort of 2781 patients: a clinical
model that included eGFR, blood pressure, and proteinuria at biopsy; and
2 full models that also contained the MEST histologic score, age,
medication use, and either racial/ethnic characteristics (white,
Japanese, or Chinese) or no racial/ethnic characteristics, to allow
application in other ethnic groups. Compared with the clinical model,
the full models with and without race/ethnicity had better R-D(2)
(26.3% and 25.3%, respectively, vs 20.3%) and AIC (6338 and 6379,
respectively, vs 6485), significant increases in C statistic from 0.78
to 0.82 and 0.81, respectively (Delta C, 0.04; 95% CI, 0.03-0.04 and
Delta C, 0.03; 95% CI, 0.02-0.03, respectively), and significant
improvement in reclassification as assessed by the NRI (0.18; 95% CI,
0.07-0.29 and 0.51; 95% CI, 0.39-0.62, respectively) and IDI (0.07;
95% CI, 0.06-0.08 and 0.06; 95% CI, 0.05-0.06, respectively). External
validation was performed in a cohort of 1146 patients. For both full
models, the C statistics (0.82; 95% CI, 0.81-0.83 with race/ethnicity;
0.81; 95% CI, 0.80-0.82 without race/ethnicity) and R-D(2) (both
35.3%) were similar or better than in the validation cohort, with
excellent calibration. Conclusions and RelevanceIn this study, the 2
full prediction models were shown to be accurate and validated methods
for predicting disease progression and patient risk stratification in
IgAN in multi-ethnic cohorts, with additional applications to clinical
trial design and biomarker research.
Συγγραφείς:
Barbour, Sean J.
Coppo, Rosanna
Zhang, Hong
Liu, Zhi-Hong
and Suzuki, Yusuke
Matsuzaki, Keiichi
Katafuchi, Ritsuko
Er,
Lee
Espino-Hernandez, Gabriela
Kim, S. Joseph
Reich, Heather
N.
Feehally, John
Cattran, Daniel C.
Russo, M. L. and
Troyanov, S.
Cook, H. T.
Roberts, I.
Tesar, V. and
Maixnerova, D.
Lundberg, S.
Gesualdo, L.
Emma, F. and
Fuiano, L.
Beltrame, G.
Rollino, C.
Amore, A.
Camilla,
R.
Peruzzi, L.
Praga, M.
Feriozzi, S.
Polci, R. and
Segoloni, G.
Colla, L.
Pani, A.
Piras, D.
Angioi, A. and
Cancarini, G.
Ravera, S.
Durlik, M.
Moggia, E.
Ballarin,
J.
Di Giulio, S.
Pugliese, F.
Serriello, I.
Caliskan, Y.
and Sever, M.
Kilicaslan, I.
Locatelli, F.
Del Vecchio, L.
and Wetzels, J. F. M.
Peters, H.
Berg, U.
Carvalho, F. and
da Costa Ferreira, A. C.
Maggio, M.
Wiecek, A. and
Ots-Rosenberg, M.
Magistroni, R.
Topaloglu, R.
Bilginer, Y.
and D'Amico, M.
Stangou, M.
Giacchino, F.
Goumenos, D. and
Kalliakmani, P.
Gerolymos, M.
Galesic, K.
Geddes, C. and
Siamopoulos, K.
Balafa, O.
Galliani, M.
Stratta, P. and
Quaglia, M.
Bergia, R.
Cravero, R.
Salvadori, M.
Cirami,
L.
Fellstrorn, B.
Smerud, H. Kloster
Ferrario, F. and
Stellato, T.
Egido, J.
Martin, C.
Floege, J.
Eitner, F.
and Lupo, A.
Bernich, P.
Mene, R.
Morosetti, M.
van
Kooten, C.
Rabelink, T.
Reinders, M. E. J.
Boria Grinyo, J.
M.
Cusinato, S.
Benozzi, L.
Savoldi, S.
Licata, C. and
Mizerska-Wasiak, M.
Martina, G.
Messuerotti, A.
Dal Canton,
A.
Esposito, C.
Migotto, C.
Triolo, G.
Mariano, F. and
Pozzi, C.
Boero, R.
Bellur, S.
Mazzucco, G.
Giannakakis,
C.
Honsova, E.
Sundelin, B.
Di Palma, A. M.
Ferrario, F.
and Gutierrez, E.
Asunis, A. M.
Barratt, J.
Tardanico, R.
and Perkowska-Ptasinska, A.
Arce Terroba, J.
Fortunato, M. and
Pantzaki, A.
Ozluk, Y.
Steenbergen, E.
Soderberg, M. and
Riispere, Z.
Furci, L.
Orhan, D.
Kipgen, D.
Casartelli,
D.
Ljubanovic, D. Galesic
Gakiopoulou, H.
Bertoni, E. and
Cannata Ortiz, P.
Karkoszka, H.
Groene, H. J.
Stoppacciaro,
A.
Bajema, I.
Bruijn, J.
Fulladosa Oliveras, X.
Maldyk,
J.
Loachim, E.
Bavbek, N.
Cook, T.
Troyanov, S. and
Alpers, C.
Amore, A.
Barratt, J.
Berthoux, F.
Bonsib, S.
and Bruijn, J.
D'Agati, V
D'Amico, G.
Emancipator, S. and
Emmal, F.
Ferrario, F.
Fervenza, F.
Florquin, S.
Fogo,
A.
Geddes, C.
Groene, H.
Haas, M.
Hill, P.
Hogg, R.
and Hsu, S.
Hunley, T.
Hladunewich
Jennette, C.
Joh, K.
and Julian, B.
Kawamura, T.
Lai, F.
Leung, C.
Li, L. and
Li, P.
Liu, Z.
Massat, A.
Mackinnon, B.
Mezzano, S. and
Schena, F.
Tomino, Y.
Walker, P.
Wang, H.
Weening, J.
and Yoshikawa, N.
Zeng, Cai-Hong
Shi, Sufang
Nogi, C. and
Suzuki, H.
Koike, K.
Hirano, K.
Kawamura, T.
Yokoo, T.
and Hanai, M.
Fukami, K.
Takahashi, K.
Yuzawa, Y.
Niwa,
M.
Yasuda, Y.
Maruyama, S.
Ichikawa, D.
Suzuki, T. and
Shirai, S.
Fukuda, A.
Fujimoto, S.
Trimarchi, H.
Int IgA
Nephropathy Network
