TY - JOUR
TI - Evaluating a New International Risk-Prediction Tool in IgA Nephropathy
AU - Barbour, Sean J.
AU - Coppo, Rosanna
AU - Zhang, Hong
AU - Liu, Zhi-Hong
AU - and Suzuki, Yusuke
AU - Matsuzaki, Keiichi
AU - Katafuchi, Ritsuko
AU - Er,
AU - Lee
AU - Espino-Hernandez, Gabriela
AU - Kim, S. Joseph
AU - Reich, Heather
AU - N.
AU - Feehally, John
AU - Cattran, Daniel C.
AU - Russo, M. L. and
AU - Troyanov, S.
AU - Cook, H. T.
AU - Roberts, I.
AU - Tesar, V. and
AU - Maixnerova, D.
AU - Lundberg, S.
AU - Gesualdo, L.
AU - Emma, F. and
AU - Fuiano, L.
AU - Beltrame, G.
AU - Rollino, C.
AU - Amore, A.
AU - Camilla,
AU - R.
AU - Peruzzi, L.
AU - Praga, M.
AU - Feriozzi, S.
AU - Polci, R. and
AU - Segoloni, G.
AU - Colla, L.
AU - Pani, A.
AU - Piras, D.
AU - Angioi, A. and
AU - Cancarini, G.
AU - Ravera, S.
AU - Durlik, M.
AU - Moggia, E.
AU - Ballarin,
AU - J.
AU - Di Giulio, S.
AU - Pugliese, F.
AU - Serriello, I.
AU - Caliskan, Y.
AU - and Sever, M.
AU - Kilicaslan, I.
AU - Locatelli, F.
AU - Del Vecchio, L.
AU - and Wetzels, J. F. M.
AU - Peters, H.
AU - Berg, U.
AU - Carvalho, F. and
AU - da Costa Ferreira, A. C.
AU - Maggio, M.
AU - Wiecek, A. and
AU - Ots-Rosenberg, M.
AU - Magistroni, R.
AU - Topaloglu, R.
AU - Bilginer, Y.
AU - and D'Amico, M.
AU - Stangou, M.
AU - Giacchino, F.
AU - Goumenos, D. and
AU - Kalliakmani, P.
AU - Gerolymos, M.
AU - Galesic, K.
AU - Geddes, C. and
AU - Siamopoulos, K.
AU - Balafa, O.
AU - Galliani, M.
AU - Stratta, P. and
AU - Quaglia, M.
AU - Bergia, R.
AU - Cravero, R.
AU - Salvadori, M.
AU - Cirami,
AU - L.
AU - Fellstrorn, B.
AU - Smerud, H. Kloster
AU - Ferrario, F. and
AU - Stellato, T.
AU - Egido, J.
AU - Martin, C.
AU - Floege, J.
AU - Eitner, F.
AU - and Lupo, A.
AU - Bernich, P.
AU - Mene, R.
AU - Morosetti, M.
AU - van
AU - Kooten, C.
AU - Rabelink, T.
AU - Reinders, M. E. J.
AU - Boria Grinyo, J.
AU - M.
AU - Cusinato, S.
AU - Benozzi, L.
AU - Savoldi, S.
AU - Licata, C. and
AU - Mizerska-Wasiak, M.
AU - Martina, G.
AU - Messuerotti, A.
AU - Dal Canton,
AU - A.
AU - Esposito, C.
AU - Migotto, C.
AU - Triolo, G.
AU - Mariano, F. and
AU - Pozzi, C.
AU - Boero, R.
AU - Bellur, S.
AU - Mazzucco, G.
AU - Giannakakis,
AU - C.
AU - Honsova, E.
AU - Sundelin, B.
AU - Di Palma, A. M.
AU - Ferrario, F.
AU - and Gutierrez, E.
AU - Asunis, A. M.
AU - Barratt, J.
AU - Tardanico, R.
AU - and Perkowska-Ptasinska, A.
AU - Arce Terroba, J.
AU - Fortunato, M. and
AU - Pantzaki, A.
AU - Ozluk, Y.
AU - Steenbergen, E.
AU - Soderberg, M. and
AU - Riispere, Z.
AU - Furci, L.
AU - Orhan, D.
AU - Kipgen, D.
AU - Casartelli,
AU - D.
AU - Ljubanovic, D. Galesic
AU - Gakiopoulou, H.
AU - Bertoni, E. and
AU - Cannata Ortiz, P.
AU - Karkoszka, H.
AU - Groene, H. J.
AU - Stoppacciaro,
AU - A.
AU - Bajema, I.
AU - Bruijn, J.
AU - Fulladosa Oliveras, X.
AU - Maldyk,
AU - J.
AU - Loachim, E.
AU - Bavbek, N.
AU - Cook, T.
AU - Troyanov, S. and
AU - Alpers, C.
AU - Amore, A.
AU - Barratt, J.
AU - Berthoux, F.
AU - Bonsib, S.
AU - and Bruijn, J.
AU - D'Agati, V
AU - D'Amico, G.
AU - Emancipator, S. and
AU - Emmal, F.
AU - Ferrario, F.
AU - Fervenza, F.
AU - Florquin, S.
AU - Fogo,
AU - A.
AU - Geddes, C.
AU - Groene, H.
AU - Haas, M.
AU - Hill, P.
AU - Hogg, R.
AU - and Hsu, S.
AU - Hunley, T.
AU - Hladunewich
AU - Jennette, C.
AU - Joh, K.
AU - and Julian, B.
AU - Kawamura, T.
AU - Lai, F.
AU - Leung, C.
AU - Li, L. and
AU - Li, P.
AU - Liu, Z.
AU - Massat, A.
AU - Mackinnon, B.
AU - Mezzano, S. and
AU - Schena, F.
AU - Tomino, Y.
AU - Walker, P.
AU - Wang, H.
AU - Weening, J.
AU - and Yoshikawa, N.
AU - Zeng, Cai-Hong
AU - Shi, Sufang
AU - Nogi, C. and
AU - Suzuki, H.
AU - Koike, K.
AU - Hirano, K.
AU - Kawamura, T.
AU - Yokoo, T.
AU - and Hanai, M.
AU - Fukami, K.
AU - Takahashi, K.
AU - Yuzawa, Y.
AU - Niwa,
AU - M.
AU - Yasuda, Y.
AU - Maruyama, S.
AU - Ichikawa, D.
AU - Suzuki, T. and
AU - Shirai, S.
AU - Fukuda, A.
AU - Fujimoto, S.
AU - Trimarchi, H.
AU - Int IgA
AU - Nephropathy Network
JO - JAMA Internal Medicine
PY - 2019
VL - 179
TODO - 7
SP - 942-952
PB - AMER MEDICAL ASSOC
SN - 2168-6106, 2168-6114
TODO - 10.1001/jamainternmed.2019.0600
TODO - null
TODO - 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.
ER -