@article{3184602,
    title = "Evaluating a New International Risk-Prediction Tool in IgA Nephropathy",
    author = "Barbour, Sean J. and Coppo, Rosanna and Zhang, Hong and Liu, Zhi-Hong and and Suzuki, Yusuke and Matsuzaki, Keiichi and Katafuchi, Ritsuko and Er, and Lee and Espino-Hernandez, Gabriela and Kim, S. Joseph and Reich, Heather and N. and Feehally, John and Cattran, Daniel C. and Russo, M. L. and and Troyanov, S. and Cook, H. T. and Roberts, I. and Tesar, V. and and Maixnerova, D. and Lundberg, S. and Gesualdo, L. and Emma, F. and and Fuiano, L. and Beltrame, G. and Rollino, C. and Amore, A. and Camilla, and R. and Peruzzi, L. and Praga, M. and Feriozzi, S. and Polci, R. and and Segoloni, G. and Colla, L. and Pani, A. and Piras, D. and Angioi, A. and and Cancarini, G. and Ravera, S. and Durlik, M. and Moggia, E. and Ballarin, and J. and Di Giulio, S. and Pugliese, F. and Serriello, I. and Caliskan, Y. and and Sever, M. and Kilicaslan, I. and Locatelli, F. and Del Vecchio, L. and and Wetzels, J. F. M. and Peters, H. and Berg, U. and Carvalho, F. and and da Costa Ferreira, A. C. and Maggio, M. and Wiecek, A. and and Ots-Rosenberg, M. and Magistroni, R. and Topaloglu, R. and Bilginer, Y. and and D'Amico, M. and Stangou, M. and Giacchino, F. and Goumenos, D. and and Kalliakmani, P. and Gerolymos, M. and Galesic, K. and Geddes, C. and and Siamopoulos, K. and Balafa, O. and Galliani, M. and Stratta, P. and and Quaglia, M. and Bergia, R. and Cravero, R. and Salvadori, M. and Cirami, and L. and Fellstrorn, B. and Smerud, H. Kloster and Ferrario, F. and and Stellato, T. and Egido, J. and Martin, C. and Floege, J. and Eitner, F. and and Lupo, A. and Bernich, P. and Mene, R. and Morosetti, M. and van and Kooten, C. and Rabelink, T. and Reinders, M. E. J. and Boria Grinyo, J. and M. and Cusinato, S. and Benozzi, L. and Savoldi, S. and Licata, C. and and Mizerska-Wasiak, M. and Martina, G. and Messuerotti, A. and Dal Canton, and A. and Esposito, C. and Migotto, C. and Triolo, G. and Mariano, F. and and Pozzi, C. and Boero, R. and Bellur, S. and Mazzucco, G. and Giannakakis, and C. and Honsova, E. and Sundelin, B. and Di Palma, A. M. and Ferrario, F. and and Gutierrez, E. and Asunis, A. M. and Barratt, J. and Tardanico, R. and and Perkowska-Ptasinska, A. and Arce Terroba, J. and Fortunato, M. and and Pantzaki, A. and Ozluk, Y. and Steenbergen, E. and Soderberg, M. and and Riispere, Z. and Furci, L. and Orhan, D. and Kipgen, D. and Casartelli, and D. and Ljubanovic, D. Galesic and Gakiopoulou, H. and Bertoni, E. and and Cannata Ortiz, P. and Karkoszka, H. and Groene, H. J. and Stoppacciaro, and A. and Bajema, I. and Bruijn, J. and Fulladosa Oliveras, X. and Maldyk, and J. and Loachim, E. and Bavbek, N. and Cook, T. and Troyanov, S. and and Alpers, C. and Amore, A. and Barratt, J. and Berthoux, F. and Bonsib, S. and and Bruijn, J. and D'Agati, V and D'Amico, G. and Emancipator, S. and and Emmal, F. and Ferrario, F. and Fervenza, F. and Florquin, S. and Fogo, and A. and Geddes, C. and Groene, H. and Haas, M. and Hill, P. and Hogg, R. and and Hsu, S. and Hunley, T. and Hladunewich and Jennette, C. and Joh, K. and and Julian, B. and Kawamura, T. and Lai, F. and Leung, C. and Li, L. and and Li, P. and Liu, Z. and Massat, A. and Mackinnon, B. and Mezzano, S. and and Schena, F. and Tomino, Y. and Walker, P. and Wang, H. and Weening, J. and and Yoshikawa, N. and Zeng, Cai-Hong and Shi, Sufang and Nogi, C. and and Suzuki, H. and Koike, K. and Hirano, K. and Kawamura, T. and Yokoo, T. and and Hanai, M. and Fukami, K. and Takahashi, K. and Yuzawa, Y. and Niwa, and M. and Yasuda, Y. and Maruyama, S. and Ichikawa, D. and Suzuki, T. and and Shirai, S. and Fukuda, A. and Fujimoto, S. and Trimarchi, H. and Int IgA and Nephropathy Network",
    journal = "JAMA Internal Medicine",
    year = "2019",
    volume = "179",
    number = "7",
    pages = "942-952",
    publisher = "AMER MEDICAL ASSOC",
    issn = "2168-6106, 2168-6114",
    doi = "10.1001/jamainternmed.2019.0600",
    abstract = "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."
}