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Risk stratification for progression of IgA nephropathy using a decision tree induction algorithm

Background. Immunoglobulin A nephropathy (IgAN) is the most common form of glomerulonephritis, and many patients are at risk of at least slow progression. However, prediction of the renal outcome in individual patients remains difficult. Methods. To develop a practical and user-friendly scheme for r...

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Autores principales: Goto, Masashi, Kawamura, Takashi, Wakai, Kenji, Ando, Masahiko, Endoh, Masayuki, Tomino, Yasuhiko
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2658733/
https://www.ncbi.nlm.nih.gov/pubmed/19017674
http://dx.doi.org/10.1093/ndt/gfn610
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author Goto, Masashi
Kawamura, Takashi
Wakai, Kenji
Ando, Masahiko
Endoh, Masayuki
Tomino, Yasuhiko
author_facet Goto, Masashi
Kawamura, Takashi
Wakai, Kenji
Ando, Masahiko
Endoh, Masayuki
Tomino, Yasuhiko
author_sort Goto, Masashi
collection PubMed
description Background. Immunoglobulin A nephropathy (IgAN) is the most common form of glomerulonephritis, and many patients are at risk of at least slow progression. However, prediction of the renal outcome in individual patients remains difficult. Methods. To develop a practical and user-friendly scheme for risk stratification of IgAN patients, data were extracted from a prospective cohort study conducted in 97 clinical units in Japan from 1995. Specifically, we examined deterioration in renal function, defined as doubling of serum creatinine, within 10 years of follow-up in 790 adult IgAN patients without substantial renal dysfunction at baseline using a decision tree induction algorithm. Results. Recursive partitioning indicated that the best single predictor of renal deterioration was severe proteinuria on urine dipstick testing, followed by hypoalbuminaemia and the presence of mild haematuria for patients with and without severe proteinuria, respectively. Serum total protein levels, diastolic blood pressure and histological grade were placed in the third tier of the decision tree model. With these six variables, patients can be readily stratified into seven risk groups whose incidence of renal deterioration within 10-year follow-up ranges from 1.0% to 51.4%. Logistic regression also identified severe proteinuria, hypoalbuminaemia and mild haematuria as significant predictors of deterioration. Areas under the receiver-operating characteristic curve for the prediction were comparable between the decision tree model and the logistic regression model [0.830 (95% confidence interval, 0.777–0.883) versus 0.808 (95% confidence interval, 0.754–0.861)]. Conclusion. Risk of substantial renal deterioration in IgAN patients can be validly estimated using six predictors obtained from clinical routine.
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spelling pubmed-26587332009-04-02 Risk stratification for progression of IgA nephropathy using a decision tree induction algorithm Goto, Masashi Kawamura, Takashi Wakai, Kenji Ando, Masahiko Endoh, Masayuki Tomino, Yasuhiko Nephrol Dial Transplant Clinical Nephrology Background. Immunoglobulin A nephropathy (IgAN) is the most common form of glomerulonephritis, and many patients are at risk of at least slow progression. However, prediction of the renal outcome in individual patients remains difficult. Methods. To develop a practical and user-friendly scheme for risk stratification of IgAN patients, data were extracted from a prospective cohort study conducted in 97 clinical units in Japan from 1995. Specifically, we examined deterioration in renal function, defined as doubling of serum creatinine, within 10 years of follow-up in 790 adult IgAN patients without substantial renal dysfunction at baseline using a decision tree induction algorithm. Results. Recursive partitioning indicated that the best single predictor of renal deterioration was severe proteinuria on urine dipstick testing, followed by hypoalbuminaemia and the presence of mild haematuria for patients with and without severe proteinuria, respectively. Serum total protein levels, diastolic blood pressure and histological grade were placed in the third tier of the decision tree model. With these six variables, patients can be readily stratified into seven risk groups whose incidence of renal deterioration within 10-year follow-up ranges from 1.0% to 51.4%. Logistic regression also identified severe proteinuria, hypoalbuminaemia and mild haematuria as significant predictors of deterioration. Areas under the receiver-operating characteristic curve for the prediction were comparable between the decision tree model and the logistic regression model [0.830 (95% confidence interval, 0.777–0.883) versus 0.808 (95% confidence interval, 0.754–0.861)]. Conclusion. Risk of substantial renal deterioration in IgAN patients can be validly estimated using six predictors obtained from clinical routine. Oxford University Press 2009-04 2008-11-17 /pmc/articles/PMC2658733/ /pubmed/19017674 http://dx.doi.org/10.1093/ndt/gfn610 Text en © The Author [2008]. http://creativecommons.org/licenses/by-nc/2.0/uk/ The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org
spellingShingle Clinical Nephrology
Goto, Masashi
Kawamura, Takashi
Wakai, Kenji
Ando, Masahiko
Endoh, Masayuki
Tomino, Yasuhiko
Risk stratification for progression of IgA nephropathy using a decision tree induction algorithm
title Risk stratification for progression of IgA nephropathy using a decision tree induction algorithm
title_full Risk stratification for progression of IgA nephropathy using a decision tree induction algorithm
title_fullStr Risk stratification for progression of IgA nephropathy using a decision tree induction algorithm
title_full_unstemmed Risk stratification for progression of IgA nephropathy using a decision tree induction algorithm
title_short Risk stratification for progression of IgA nephropathy using a decision tree induction algorithm
title_sort risk stratification for progression of iga nephropathy using a decision tree induction algorithm
topic Clinical Nephrology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2658733/
https://www.ncbi.nlm.nih.gov/pubmed/19017674
http://dx.doi.org/10.1093/ndt/gfn610
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