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 language | English |
|---|---|
| Pages (from-to) | 167-175 |
| Number of pages | 9 |
| Journal | Kidney International |
| Volume | 89 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 1 2016 |
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Keywords
- glomerular disease
- IgA nephropathy
- renal pathology
ASJC Scopus subject areas
- Nephrology
Cite this
The MEST score provides earlier risk prediction in lgA nephropathy. / Barbour, Sean J.; Espino-Hernandez, Gabriela; Reich, Heather N.; Coppo, Rosanna; Roberts, Ian S D; Feehally, John; Herzenberg, Andrew M.; Cattran, Daniel C.; Bavbek, N.; Cook, T.; Troyanov, Stéphan; Alpers, Charles E.; Amore, A.; Barratt, Jonathan; Berthoux, Francois; Bonsib, Stephen; Bruijn, J.; D'Agati, V. D.; D'Amico, G.; Emancipator, Steven; Emmal, F.; Ferrario, Francesca; Fervenza, F.; Florquin, Sandrine; Fogo, Agnes; Geddes, C.; Groene, H.; Haas, Mark; Hill, Prue A.; Hogg, R.; Hsu, Stephen I.; Hunley, T.; Hladunewich, M.; Jennette, C.; Joh, Kensuke; Julian, Bruce A.; Kawamura, Tetsuya; Lai, Fernand M.; Leung, C.; Li, Lei Shi; Li, P.; Liu, Z. H.; Massat, A.; MacKinnon, Bruce; Mezzano, Sergio; Schena, Francesco Paolo; Tomino, Yasuhiko; Walker, Patrick D.; Wang, H.; Weening, Jan J.; Yoshikawa, N.; Zhang, H.; Coppo, R.; Troyanov, S.; Cattran, D. C.; Cook, H. T.; Feehally, J.; Roberts, Ian S D; Tesar, Vladimir; Maixnerova, D.; Lundberg, S.; Gesualdo, L.; Emma, Francesco; Fuiano, L.; Beltrame, G.; Rollino, Cristiana; Amore, Alessandro; Camilla, Roberta; Peruzzi, L.; Praga, Manuel; Feriozzi, Sandro; Polci, R.; Segoloni, G.; Colla, L.; Pani, Antonello; Angioi, A.; Piras, L.; Cancarini, Giovanni; Ravera, S.; Durlik, Magalena; Moggia, Elisabetta; Ballarin, J.; Di Giulio, S.; Pugliese, F.; Serriello, I.; Caliskan, Y.; Sever, M.; Kilicaslan, I.; Locatelli, F.; Del Vecchio, Lucia; Wetzels, J. F M; Peters, H.; Berg, U.; Carvalho, F.; Da Costa Ferreira, A. C.; Maggio, M.; Wiecek, A.; Ots-Rosenberg, M.; Magistroni, Riccardo; Topaloglu, R.; Bilginer, Y.; D'Amico, M.; Stangou, M.; Giacchino, F.; Goumenos, D.; Kalliakmani, P.; Gerolymos, M.; Galesic, K.; Geddes, C.; Siamopoulos, K.; Balafa, O.; Galliani, M.; Stratta, P.; Quaglia, Marco; Bergia, R.; Cravero, R.; Salvadori, M.; Cirami, L.; Fellstrom, B.; Kloster Smerud, H.; Ferrario, F.; Stellato, T.; Egido, J.; Martin, C.; Floege, J.; Eitner, F.; Lupo, A.; Bernich, P.; Menè, P.; Morosetti, M.; Van Kooten, C.; Rabelink, T.; Reinders, M. E J; Boria Grinyo, J. M.; Cusinato, S.; Benozzi, L.; Savoldi, Silvana; Licata, C.; Mizerska Wasiak, M.; Martina, G.; Messuerotti, A.; Dal Canton, Antonio; Esposito, Ciro; Migotto, C.; Triolo, G.; Mariano, F.; Pozzi, C.; Boero, R.; Bellur, Shubha; Mazzucco, Gianna; Giannakakis, Costantinos; Honsova, Eva; Sundelin, B. Brigitta; Di Palma, A. M.; Ferrario, Franco; Gutierrez, Eduardo; Asunis, Anna Maria; Barratt, Jonathan; Tardanico, Regina; Perkowska-Ptasinska, Agnieszka; Arce Terroba, J.; Fortunato, M.; Pantzaki, A.; Ozluk, Y.; Steenbergen, Eric; Soderberg, M.; Riispere, Z.; Furci, Luciana; Orhan, D.; Kipgen, D.; Casartelli, D.; Galesic Ljubanovic, D.; Gakiopoulou, H.; Bertoni, E.; Cannata Ortiz, P.; Karkoszka, H.; Groene, H. J.; Stoppacciaro, Antonella; Bajema, I.; Bruijn, J.; Fulladosa Oliveras, X.; Maldyk, J.; Ioachim, E.
In: Kidney International, Vol. 89, No. 1, 01.01.2016, p. 167-175.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - The MEST score provides earlier risk prediction in lgA nephropathy
AU - Barbour, Sean J.
AU - Espino-Hernandez, Gabriela
AU - Reich, Heather N.
AU - Coppo, Rosanna
AU - Roberts, Ian S D
AU - Feehally, John
AU - Herzenberg, Andrew M.
AU - Cattran, Daniel C.
AU - Bavbek, N.
AU - Cook, T.
AU - Troyanov, Stéphan
AU - Alpers, Charles E.
AU - Amore, A.
AU - Barratt, Jonathan
AU - Berthoux, Francois
AU - Bonsib, Stephen
AU - Bruijn, J.
AU - D'Agati, V. D.
AU - D'Amico, G.
AU - Emancipator, Steven
AU - Emmal, F.
AU - Ferrario, Francesca
AU - Fervenza, F.
AU - Florquin, Sandrine
AU - Fogo, Agnes
AU - Geddes, C.
AU - Groene, H.
AU - Haas, Mark
AU - Hill, Prue A.
AU - Hogg, R.
AU - Hsu, Stephen I.
AU - Hunley, T.
AU - Hladunewich, M.
AU - Jennette, C.
AU - Joh, Kensuke
AU - Julian, Bruce A.
AU - Kawamura, Tetsuya
AU - Lai, Fernand M.
AU - Leung, C.
AU - Li, Lei Shi
AU - Li, P.
AU - Liu, Z. H.
AU - Massat, A.
AU - MacKinnon, Bruce
AU - Mezzano, Sergio
AU - Schena, Francesco Paolo
AU - Tomino, Yasuhiko
AU - Walker, Patrick D.
AU - Wang, H.
AU - Weening, Jan J.
AU - Yoshikawa, N.
AU - Zhang, H.
AU - Coppo, R.
AU - Troyanov, S.
AU - Cattran, D. C.
AU - Cook, H. T.
AU - Feehally, J.
AU - Roberts, Ian S D
AU - Tesar, Vladimir
AU - Maixnerova, D.
AU - Lundberg, S.
AU - Gesualdo, L.
AU - Emma, Francesco
AU - Fuiano, L.
AU - Beltrame, G.
AU - Rollino, Cristiana
AU - Amore, Alessandro
AU - Camilla, Roberta
AU - Peruzzi, L.
AU - Praga, Manuel
AU - Feriozzi, Sandro
AU - Polci, R.
AU - Segoloni, G.
AU - Colla, L.
AU - Pani, Antonello
AU - Angioi, A.
AU - Piras, L.
AU - Cancarini, Giovanni
AU - Ravera, S.
AU - Durlik, Magalena
AU - Moggia, Elisabetta
AU - Ballarin, J.
AU - Di Giulio, S.
AU - Pugliese, F.
AU - Serriello, I.
AU - Caliskan, Y.
AU - Sever, M.
AU - Kilicaslan, I.
AU - Locatelli, F.
AU - Del Vecchio, Lucia
AU - Wetzels, J. F M
AU - Peters, H.
AU - Berg, U.
AU - Carvalho, F.
AU - Da Costa Ferreira, A. C.
AU - Maggio, M.
AU - Wiecek, A.
AU - Ots-Rosenberg, M.
AU - Magistroni, Riccardo
AU - Topaloglu, R.
AU - Bilginer, Y.
AU - D'Amico, M.
AU - Stangou, M.
AU - Giacchino, F.
AU - Goumenos, D.
AU - Kalliakmani, P.
AU - Gerolymos, M.
AU - Galesic, K.
AU - Geddes, C.
AU - Siamopoulos, K.
AU - Balafa, O.
AU - Galliani, M.
AU - Stratta, P.
AU - Quaglia, Marco
AU - Bergia, R.
AU - Cravero, R.
AU - Salvadori, M.
AU - Cirami, L.
AU - Fellstrom, B.
AU - Kloster Smerud, H.
AU - Ferrario, F.
AU - Stellato, T.
AU - Egido, J.
AU - Martin, C.
AU - Floege, J.
AU - Eitner, F.
AU - Lupo, A.
AU - Bernich, P.
AU - Menè, P.
AU - Morosetti, M.
AU - Van Kooten, C.
AU - Rabelink, T.
AU - Reinders, M. E J
AU - Boria Grinyo, J. M.
AU - Cusinato, S.
AU - Benozzi, L.
AU - Savoldi, Silvana
AU - Licata, C.
AU - Mizerska Wasiak, M.
AU - Martina, G.
AU - Messuerotti, A.
AU - Dal Canton, Antonio
AU - Esposito, Ciro
AU - Migotto, C.
AU - Triolo, G.
AU - Mariano, F.
AU - Pozzi, C.
AU - Boero, R.
AU - Bellur, Shubha
AU - Mazzucco, Gianna
AU - Giannakakis, Costantinos
AU - Honsova, Eva
AU - Sundelin, B. Brigitta
AU - Di Palma, A. M.
AU - Ferrario, Franco
AU - Gutierrez, Eduardo
AU - Asunis, Anna Maria
AU - Barratt, Jonathan
AU - Tardanico, Regina
AU - Perkowska-Ptasinska, Agnieszka
AU - Arce Terroba, J.
AU - Fortunato, M.
AU - Pantzaki, A.
AU - Ozluk, Y.
AU - Steenbergen, Eric
AU - Soderberg, M.
AU - Riispere, Z.
AU - Furci, Luciana
AU - Orhan, D.
AU - Kipgen, D.
AU - Casartelli, D.
AU - Galesic Ljubanovic, D.
AU - Gakiopoulou, H.
AU - Bertoni, E.
AU - Cannata Ortiz, P.
AU - Karkoszka, H.
AU - Groene, H. J.
AU - Stoppacciaro, Antonella
AU - Bajema, I.
AU - Bruijn, J.
AU - Fulladosa Oliveras, X.
AU - Maldyk, J.
AU - Ioachim, E.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - 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.
AB - 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.
KW - glomerular disease
KW - IgA nephropathy
KW - renal pathology
UR - http://www.scopus.com/inward/record.url?scp=84945559550&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84945559550&partnerID=8YFLogxK
U2 - 10.1038/ki.2015.322
DO - 10.1038/ki.2015.322
M3 - Article
VL - 89
SP - 167
EP - 175
JO - Kidney International
JF - Kidney International
SN - 0085-2538
IS - 1
ER -