Risk Stratification of Patients With IgA Nephropathy

Department of Medicine, Division of Nephrology, University of British Columbia, Vancouver, British Columbia, Canada.
American Journal of Kidney Diseases (Impact Factor: 5.9). 04/2012; 59(6):865-73. DOI: 10.1053/j.ajkd.2012.02.326
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In this review, we summarize recent advances in the risk stratification of patients with immunoglobulin A (IgA) nephropathy. Several clinical variables have consistent and independent associations with worse kidney prognosis, including blood pressure, proteinuria, and baseline kidney function. Although one-time cross-sectional assessments of blood pressure and proteinuria are important, a more thorough understanding of risk can be achieved when these variables are considered over a follow-up period. IgA nephropathy is unique compared with other glomerular diseases in that a much lower threshold of proteinuria (protein excretion, 1 g/d) is associated with glomerular filtration rate (GFR) loss. Controlling proteinuria and blood pressure over time is important to reduce the risk of future loss of kidney function. The recently described Oxford classification has helped standardize the pathologic characterization of IgA nephropathy using a scoring system that is readily reproducible and associated with increased risk of GFR loss independent of clinical variables. We suggest an approach to risk stratification in IgA nephropathy when considering potential treatment with immunosuppression. Despite our current understanding of risk stratification in IgA nephropathy, the ability to accurately predict individual patient-level risk currently is limited, and further research into additional biomarkers or risk prediction tools is needed to improve the care of patients with IgA nephropathy.

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Available from: Heather N Reich, Sep 02, 2015
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    • "24-h proteinuria might thus be not completely attributable to IgAN in these particular cases. The importance of proteinuria as a predictor of decreasing estimated glomerular filtration rate (eGFR) was highlighted by previous studies (Moriyama et al. 2014; Bartosik et al. 2001; Barbour and Reich 2012). Thus maintenance of 24-h proteinuria levels below 1 g/24 h is one of the targets in the management of IgAN. "
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    ABSTRACT: IgA nephropathy (IgAN) is th e commonest primary glomerular disease worldwide. Studies on its prevalence in Brazil are however scarce. Databases and clinical records from 10 reference centres were retrospectively reviewed. Clinical and laboratory features at the moment of the biopsy were retrieved (age, gender, presence of hematuria, serum creatinine [mg/dL], proteinuria [g/24 h]). Renal biopsy findings were classified according to Haas single grade classification scheme and the Oxford Classification of IgAN. 600 cases of IgAN were identified, of which 568 (94.7 %) were on native kidneys. Male to female ratio was 1.24:1. Patients averaged 32.76 ± 15.12 years old (range 4-89, median 32). Proteinuria and hematuria were observed, respectively in 56.63 and 72.29 % of patients. The association of both these findings occurred in 37.95 % of the cases. Serum creatinine averaged 1.65 ± 0.67 mg/dL (median 1.5 mg/dL) at diagnosis. Segmental sclerosis and mesangial hypercellularity were the main glomerular findings (47.6 and 46.2 %) The commonest combination by Oxford Classification of IgAN, was M0 E0 S0 T0 (22.4 %). Chronic tubulo-interstitial lesions with an extension wider than 25 % of the renal cortex could be identified in 32.2 % of the cases. Tubular atrophy and interstitial fibrosis were more strongly associated with higher 24-h proteinuria and serum creatinine levels. Segmental sclerosis (S1) showed a stronger tendency of association with the presence of tubulo-interstitial lesions (T1 and T2) than other glomerular variables. To the best of our knowledge this is the largest series of IgAN in Brazil. It depicts the main biopsy findings and their possible clinical correlates. Our set of data is comparable to previous reports.
    SpringerPlus 12/2015; 4(1). DOI:10.1186/s40064-015-1323-x
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    • "This disease remains a leading cause of end-stage kidney disease (ESKD) thus requiring renal replacement therapy with dialysis or kidney transplantation. The ability to accurately predict individual patient-level risk is still limited, and the need for novel prediction tools of ESKD risk degree to improve the care of patients with IgAN has been widely emphasized (Barbour & Reich, 2012). Dialysis care is a particularly complex task and multiple factors may influence patient survival. "
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    ABSTRACT: Objective: IgA Nephropathy (IgAN) is a common kidney disease which may entail renal failure, known as End Stage Kidney Disease (ESKD). One of the major difficulties dealing with this disease is to predict the time of the long-term prognosis for a patient at the time of diagnosis. In fact, the progression of IgAN to ESKD depends on an intricate interrelationship between clinical and laboratory findings. Therefore, the objective of this work has been the selection of the best data mining tool to build a model able to predict (I) if a patient with a biopsy proven IgAN will reach ESKD and (II) if a patient will reach the ESKD before or after 5 years. Material and Methods: The largest available cohort study worldwide on IgAN has been used to design and compare several data-driven models. The complete dataset was composed of 1174 records collected from Italian, Norwegian, and Japanese IgAN patients, in the last 30 years. The data mining tools considered in this work were artificial neural networks (ANNs), neuro fuzzy systems (NFSs), support vector machines (SVMs), and decision trees (DTs). A 10-fold cross validation was used to evaluate unbiased performances for all the models. Results: An extensive model comparison based on accuracy, precision, recall, and f-measure was provided. Overall, the results indicate that ANNs can provide superior performance compared to the other models. The ANN for time-to- ESKD prediction is characterized by accuracy, precision, recall, and f-measure greater than 90%. The ANN for ESKD prediction has accuracy greater than 90% as well as precision, recall, and f-measure for the class of patients not reaching ESKD, while precision, recall, and f-measure for the class of patients reaching ESKD are slightly lower. The obtained model has been implemented in a Web-based decision support system (DSS). Conclusions: The extraction of novel knowledge from clinical data and the definition of predictive models to support diagnosis, prognosis, and therapy is becoming an essential tool for researchers and clinical practitioners in medicine. The proposed comparative study of several data mining models for the outcome prediction in IgAN patients, using a large dataset of clinical records from three different countries, provides an insight into the relative prediction ability of the considered methods applied to such a disease.
    Computers in Biology and Medicine 09/2015; DOI:10.1016/j.compbiomed.2015.09.003 · 1.24 Impact Factor
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    • "The initial manifestation of disease is frequently synpharyngitic hematuria, that is, macroscopic hematuria concurrent with upper respiratory tract infection [1, 2]. Progressive renal damage often culminates in end-stage renal disease (ESRD) that requires dialysis or transplantation as renal replacement therapy [3, 4]. In patients undergoing renal transplantation, the high rate of recurrence, up to 50–60%, suggests that the disease is of extrarenal origin [5]. "
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    ABSTRACT: Immunoglobulin A (IgA) nephropathy (IgAN), the leading cause of primary glomerulonephritis, is characterized by IgA1-containing immunodeposits in the glomeruli. IgAN is a chronic disease, with up to 40% of patients progressing to end-stage renal disease, with no disease-specific treatment. Multiple studies of the origin of the glomerular immunodeposits have linked elevated circulating levels of aberrantly glycosylated IgA1 (galactose-deficient in some O-glycans; Gd-IgA1) with formation of nephritogenic Gd-IgA1-containing immune complexes. Gd-IgA1 is recognized as an autoantigen in susceptible individuals by anti-glycan autoantibodies, resulting in immune complexes that may ultimately deposit in the kidney and induce glomerular injury. Genetic studies have revealed that an elevated level of Gd-IgA1 in the circulation of IgAN patients is a hereditable trait. Moreover, recent genome-wide association studies have identified several immunity-related loci that associated with IgAN. Production of Gd-IgA1 by IgA1-secreting cells of IgAN patients has been attributed to abnormal expression and activity of several key glycosyltransferases. Substantial evidence is emerging that abnormal signaling in IgA1-producing cells is related to the production of Gd-IgA1. As Gd-IgA1 is the key autoantigen in IgAN, understanding the genetic, biochemical, and environmental aspects of the abnormal signaling in IgA1-producing cells will provide insight into possible targets for future disease-specific therapy.
    Research Journal of Immunology 07/2014; 2014:197548. DOI:10.1155/2014/197548
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