The MEST score provides earlier risk prediction in lgA nephropathy

Sean J. Barbour, Gabriela Espino-Hernandez, Heather N. Reich, Rosanna Coppo, Ian S D Roberts, John Feehally, Andrew M. Herzenberg, Daniel C. Cattran, N. Bavbek, T. Cook, Stéphan Troyanov, Charles E. Alpers, A. Amore, Jonathan Barratt, Francois Berthoux, Stephen Bonsib, J. Bruijn, V. D. D'Agati, G. D'Amico, Steven EmancipatorF. Emmal, Francesca Ferrario, F. Fervenza, Sandrine Florquin, Agnes Fogo, C. Geddes, H. Groene, Mark Haas, Prue A. Hill, R. Hogg, Stephen I. Hsu, T. Hunley, M. Hladunewich, C. Jennette, Kensuke Joh, Bruce A. Julian, Tetsuya Kawamura, Fernand M. Lai, C. Leung, Lei Shi Li, P. Li, Z. H. Liu, A. Massat, Bruce MacKinnon, Sergio Mezzano, Francesco Paolo Schena, Yasuhiko Tomino, Patrick D. Walker, H. Wang, Jan J. Weening, N. Yoshikawa, H. Zhang, R. Coppo, S. Troyanov, D. C. Cattran, H. T. Cook, J. Feehally, Ian S D Roberts, Vladimir Tesar, D. Maixnerova, S. Lundberg, L. Gesualdo, Francesco Emma, L. Fuiano, G. Beltrame, Cristiana Rollino, Alessandro Amore, Roberta Camilla, L. Peruzzi, Manuel Praga, Sandro Feriozzi, R. Polci, G. Segoloni, L. Colla, Antonello Pani, A. Angioi, L. Piras, Giovanni Cancarini, S. Ravera, Magalena Durlik, Elisabetta Moggia, J. Ballarin, S. Di Giulio, F. Pugliese, I. Serriello, Y. Caliskan, M. Sever, I. Kilicaslan, F. Locatelli, Lucia Del Vecchio, J. F M Wetzels, H. Peters, U. Berg, F. Carvalho, A. C. Da Costa Ferreira, M. Maggio, A. Wiecek, M. Ots-Rosenberg, Riccardo Magistroni, R. Topaloglu, Y. Bilginer, M. D'Amico, M. Stangou, F. Giacchino, D. Goumenos, P. Kalliakmani, M. Gerolymos, K. Galesic, C. Geddes, K. Siamopoulos, O. Balafa, M. Galliani, P. Stratta, Marco Quaglia, R. Bergia, R. Cravero, M. Salvadori, L. Cirami, B. Fellstrom, H. Kloster Smerud, F. Ferrario, T. Stellato, J. Egido, C. Martin, J. Floege, F. Eitner, A. Lupo, P. Bernich, P. Menè, M. Morosetti, C. Van Kooten, T. Rabelink, M. E J Reinders, J. M. Boria Grinyo, S. Cusinato, L. Benozzi, Silvana Savoldi, C. Licata, M. Mizerska Wasiak, G. Martina, A. Messuerotti, Antonio Dal Canton, Ciro Esposito, C. Migotto, G. Triolo, F. Mariano, C. Pozzi, R. Boero, Shubha Bellur, Gianna Mazzucco, Costantinos Giannakakis, Eva Honsova, B. Brigitta Sundelin, A. M. Di Palma, Franco Ferrario, Eduardo Gutierrez, Anna Maria Asunis, Jonathan Barratt, Regina Tardanico, Agnieszka Perkowska-Ptasinska, J. Arce Terroba, M. Fortunato, A. Pantzaki, Y. Ozluk, Eric Steenbergen, M. Soderberg, Z. Riispere, Luciana Furci, D. Orhan, D. Kipgen, D. Casartelli, D. Galesic Ljubanovic, H. Gakiopoulou, E. Bertoni, P. Cannata Ortiz, H. Karkoszka, H. J. Groene, Antonella Stoppacciaro, I. Bajema, J. Bruijn, X. Fulladosa Oliveras, J. Maldyk, E. Ioachim

Research output: Contribution to journalArticle

Abstract

The Oxford Classification of IgA nephropathy (IgAN) includes the following four histologic components: mesangial (M) and endocapillary (E) hypercellularity, segmental sclerosis (S) and interstitial fibrosis/tubular atrophy (T). These combine to form the MEST score and are independently associated with renal outcome. Current prediction and risk stratification in IgAN requires clinical data over 2 years of follow-up. Using modern prediction tools, we examined whether combining MEST with cross-sectional clinical data at biopsy provides earlier risk prediction in IgAN than current best methods that use 2 years of follow-up data. We used a cohort of 901 adults with IgAN from the Oxford derivation and North American validation studies and the VALIGA study followed for a median of 5.6 years to analyze the primary outcome (50% decrease in eGFR or ESRD) using Cox regression models. Covariates of clinical data at biopsy (eGFR, proteinuria, MAP) with or without MEST, and then 2-year clinical data alone (2-year average of proteinuria/MAP, eGFR at biopsy) were considered. There was significant improvement in prediction by adding MEST to clinical data at biopsy. The combination predicted the outcome as well as the 2-year clinical data alone, with comparable calibration curves. This effect did not change in subgroups treated or not with RAS blockade or immunosuppression. Thus, combining the MEST score with cross-sectional clinical data at biopsy provides earlier risk prediction in IgAN than our current best methods.

Original languageEnglish
Pages (from-to)167-175
Number of pages9
JournalKidney International
Volume89
Issue number1
DOIs
Publication statusPublished - Jan 1 2016

Keywords

  • glomerular disease
  • IgA nephropathy
  • renal pathology

ASJC Scopus subject areas

  • Nephrology

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    Barbour, S. J., Espino-Hernandez, G., Reich, H. N., Coppo, R., Roberts, I. S. D., Feehally, J., Herzenberg, A. M., Cattran, D. C., Bavbek, N., Cook, T., Troyanov, S., Alpers, C. E., Amore, A., Barratt, J., Berthoux, F., Bonsib, S., Bruijn, J., D'Agati, V. D., D'Amico, G., ... Ioachim, E. (2016). The MEST score provides earlier risk prediction in lgA nephropathy. Kidney International, 89(1), 167-175. https://doi.org/10.1038/ki.2015.322