Oxford Classification of IgA nephropathy 2016: an update from the IgA Nephropathy Classification Working Group
TL;DR: It has now been shown that combining the MEST score with clinical data at biopsy provides the same predictive power as monitoring clinical data for 2 years; this requires further evaluation to assess earlier effective treatment intervention.
About: This article is published in Kidney International.The article was published on 2017-05-01 and is currently open access. It has received 660 citations till now. The article focuses on the topics: Retrospective cohort study.
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Leiden University Medical Center1, University of Washington2, Harvard University3, Imperial College London4, Columbia University Medical Center5, Cedars-Sinai Medical Center6, University of North Carolina at Chapel Hill7, Tohoku University8, University of Oxford9, Cornell University10, Mayo Clinic11, Vanderbilt University12
TL;DR: A consensus report pertaining to the improved clarity of definitions and classification of glomerular lesions in lupus nephritis that derived from a meeting of 18 members of an international nephropathology working group in Leiden, Netherlands, in 2016 is presented.
447 citations
TL;DR: Two 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.
Abstract: Importance Although 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. Objective To 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 participants We 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 measures Cox 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 R2D measure, Akaike information criterion (AIC), C statistic, continuous net reclassification improvement (NRI), integrated discrimination improvement (IDI), and calibration plots. Results The 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 R2D (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 (ΔC, 0.04; 95% CI, 0.03-0.04 and ΔC, 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 R2D (both 35.3%) were similar or better than in the validation cohort, with excellent calibration. Conclusions and relevance In 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.
218 citations
TL;DR: Data suggest that lnc-TSI reduced renal fibrogenesis through negative regulation of the TGF-β/Smad pathway, a common outcome of almost all progressive chronic kidney diseases.
Abstract: Transforming growth factor-β (TGF-β) is a well-established central mediator of renal fibrosis, a common outcome of almost all progressive chronic kidney diseases. Here, we identified a poorly conserved and kidney-enriched long noncoding RNA in TGF-β1-stimulated human tubular epithelial cells and fibrotic kidneys, which we termed TGF-β/Smad3-interacting long noncoding RNA (lnc-TSI). Lnc-TSI was transcriptionally regulated by Smad3 and specifically inhibited TGF-β-induced Smad3 phosphorylation and downstream profibrotic gene expression. Lnc-TSI acted by binding with the MH2 domain of Smad3, blocking the interaction of Smad3 with TGF-β receptor I independent of Smad7. Delivery of human lnc-TSI into unilateral ureteral obstruction (UUO) mice, a well-established model of renal fibrosis, inhibited phosphorylation of Smad3 in the kidney and attenuated renal fibrosis. In a cohort of 58 patients with biopsy-confirmed IgA nephropathy (IgAN), lnc-TSI renal expression negatively correlated with the renal fibrosis index (r = -0.56, P < 0.001) after adjusting for cofounders. In a longitudinal study, 32 IgAN patients with low expression of renal lnc-TSI at initial biopsy had more pronounced increases in their renal fibrosis index and experienced stronger declines in renal function at repeat biopsy at a mean of 48 months of follow-up. These data suggest that lnc-TSI reduced renal fibrogenesis through negative regulation of the TGF-β/Smad pathway.
130 citations
Center for Drug Evaluation and Research1, Tufts Medical Center2, RWTH Aachen University3, The George Institute for Global Health4, University of Nice Sophia Antipolis5, University of Leicester6, University Health Network7, University of North Carolina at Chapel Hill8, The Ohio State University Wexner Medical Center9, American Society of Nephrology10, University of Minnesota11
TL;DR: Data support the use of proteinuria reduction as a reasonably likely surrogate end point for a treatment's effect on progression to ESKD in IgAN, according to a critical review of the data.
Abstract: IgA nephropathy (IgAN) is an important cause of ESKD for which there are no approved therapies. A challenge for evaluating treatments for IgAN is the usual long time course for progression to ESKD. The aim of this Kidney Health Initiative project was to identify surrogate end points that could serve as reliable predictors of a treatment’s effect on long-term kidney outcomes in IgAN and be used as a basis for approval. Proteinuria was identified as the most widely recognized and well studied risk factor for progression to ESKD in IgAN. The workgroup performed a critical review of the data on proteinuria reduction as a surrogate end point for a treatment’s effect on progression to ESKD in IgAN. Epidemiologic data indicate a strong and consistent relationship between the level and duration of proteinuria and loss of kidney function. Trial-level analyses of data from 13 controlled trials also show an association between treatment effects on percent reduction of proteinuria and treatment effects on a composite of time to doubling of serum creatinine, ESKD, or death. We conclude that data support the use of proteinuria reduction as a reasonably likely surrogate end point for a treatment’s effect on progression to ESKD in IgAN. In the United States, reasonably likely surrogate end points can be used as a basis for accelerated approval of therapies intended to treat serious or life-threatening conditions, such as IgAN. The clinical benefit of products approved under this program would need to be verified in a postmarketing confirmatory trial.
108 citations
TL;DR: A prediction model using routinely available characteristics and based on the combination of a machine learning algorithm and survival analysis can stratify risk for kidney disease progression in the setting of IgAN.
102 citations
References
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University of Toronto1, University of Turin2, Imperial College London3, Leicester General Hospital4, John Radcliffe Hospital5, Université de Montréal6, University of Washington7, LSU Health Sciences Center Shreveport8, Leiden University9, Columbia University10, Case Western Reserve University11, Mayo Clinic12, University of Amsterdam13, Vanderbilt University14, Western Infirmary15, German Cancer Research Center16, Johns Hopkins University17, St. Vincent's Health System18, Scott & White Hospital19, University of Florida20, University of North Carolina at Chapel Hill21, University of Alabama at Birmingham22, Jikei University School of Medicine23, The Chinese University of Hong Kong24, Nanjing University25, Austral University of Chile26, Juntendo University27, Peking University28, Erasmus University Rotterdam29, Wakayama Medical University30
TL;DR: In this article, a new classification for IgA nephropathy is presented by an international consensus working group and the goal of this new system was to identify specific pathological features that more accurately predict risk of progression of renal disease.
994 citations
TL;DR: The VALIGA study provides a validation of the Oxford classification in a large European cohort of IgAN patients across the whole spectrum of the disease, and shows the independent predictive value of pathology MEST score is reduced by glucocorticoid/immunosuppressive therapy.
345 citations
TL;DR: MAP and severity of proteinuria over time are the most important prognostic indicators of IgA nephropathy, and the combination of best accuracy of prediction and shortest observation time using these two parameters was reached between the second and third years of follow-up.
332 citations
Cedars-Sinai Medical Center1, Radboud University Nijmegen2, Nanjing University3, University of Washington4, University of Leicester5, University Health Network6, Imperial College London7, Medical University of Warsaw8, University of Oxford9, Federal University of São Paulo10, Fujita Health University11, Peking University12, Université de Montréal13
TL;DR: A large IgA nephropathy cohort pooled from four retrospective studies addressed crescents as a predictor of renal outcomes and determined whether the fraction of crescent-containing glomeruli associates with survival from either a ≥50% decline in eGFR or ESRD (combined event) adjusting for covariates used in the original Oxford study.
Abstract: The Oxford Classification of IgA nephropathy does not account for glomerular crescents. However, studies that reported no independent predictive role of crescents on renal outcomes excluded individuals with severe renal insufficiency. In a large IgA nephropathy cohort pooled from four retrospective studies, we addressed crescents as a predictor of renal outcomes and determined whether the fraction of crescent-containing glomeruli associates with survival from either a ≥50% decline in eGFR or ESRD (combined event) adjusting for covariates used in the original Oxford study. The 3096 subjects studied had an initial mean±SD eGFR of 78±29 ml/min per 1.73 m2 and median (interquartile range) proteinuria of 1.2 (0.7-2.3) g/d, and 36% of subjects had cellular or fibrocellular crescents. Overall, crescents predicted a higher risk of a combined event, although this remained significant only in patients not receiving immunosuppression. Having crescents in at least one sixth or one fourth of glomeruli associated with a hazard ratio (95% confidence interval) for a combined event of 1.63 (1.10 to 2.43) or 2.29 (1.35 to 3.91), respectively, in all individuals. Furthermore, having crescents in at least one fourth of glomeruli independently associated with a combined event in patients receiving and not receiving immunosuppression. We propose adding the following crescent scores to the Oxford Classification: C0 (no crescents); C1 (crescents in less than one fourth of glomeruli), identifying patients at increased risk of poor outcome without immunosuppression; and C2 (crescents in one fourth or more of glomeruli), identifying patients at even greater risk of progression, even with immunosuppression.
212 citations
TL;DR: Serum levels of IgG and IgA autoantibodies strongly associate with the progression of IgAN nephropathy, and increasing levels correlated with worse clinical outcomes.
Abstract: Mesangial and circulating IgA1 with aberrantly glycosylated hinge region O-glycans characterize IgA nephropathy (IgAN). Unlike healthy individuals, some IgA1 is galactose deficient in patients with IgAN, leaving terminal N-acetylgalactosamine residues in the hinge region exposed. Circulating autoantibodies that recognize such galactose-deficient IgA1 as an autoantigen, or the levels of the autoantigen itself, may allow prediction of disease progression. Here, we analyzed serum samples obtained at diagnosis for autoantigen and autoantibodies from 97 patients with IgAN selected from our prospective cohort according to their absolute renal risk for progression to dialysis or death (0, very low; 1, low; 2, high; 3, very high). We also analyzed samples from controls comprising 30 healthy volunteers and 30 patients with non-IgAN disease. The mean follow-up was 13.8 years. We found that mean serum levels of total autoantigen, normalized IgG autoantibody, and total IgA autoantibody were significantly higher in patients than in the combined controls (all P≤0.01). Furthermore, increasing levels correlated with worse clinical outcomes. In Cox regression and Kaplan-Meier analyses, IgG autoantibody levels ≥1.33 predicted dialysis or death (both P≤0.01). In conclusion, these data suggest that serum levels of IgG and IgA autoantibodies strongly associate with the progression of IgAN nephropathy.
202 citations