Naslov
The MEST score provides earlier risk prediction in lgA nephropathy

Autori
Barbour SJ ; Espino-Hernandez G ; Reich HN ; Coppo R ; Roberts IS ; Feehally J ; Herzenberg AM ; Cattran DC ; Oxford Derivation, North American Validation and VALIGA Consortia ; Oxford Derivation North American Validation and VALIGA Consortia.

Izvornik
Kidney international (0085-2538) 89 (2016), 1; 167-175

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
IgA nephropathy ; glomerular disease ; renal pathology

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti

Napomena
Group Author(s): VALIGA Study (hrvatski suradnici: Krešimir Galešić i Danica Galešić-Ljubanović)

POVEZANOST RADA