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

• Published in: Nephrology, dialysis, transplantation Vol. 24; no. 4; pp. 1242 - 1247
• Main Authors: Goto, Masashi, Kawamura, Takashi, Wakai, Kenji, Ando, Masahiko, Endoh, Masayuki, Tomino, Yasuhiko
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.04.2009; Oxford Publishing Limited (England)
• Subjects: Adult; Algorithms; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy; Biological and medical sciences; Clinical Nephrology; cohort studies; Decision Trees; Disease Progression; Emergency and intensive care: renal failure. Dialysis management; Female; Glomerulonephritis; Glomerulonephritis, IGA - diagnosis; Humans; IgA nephropathy; Intensive care medicine; Male; Medical sciences; Nephrology. Urinary tract diseases; Nephropathies. Renovascular diseases. Renal failure; Prognosis; Risk Assessment; risk factors; ROC Curve; Young Adult; cohort studies; risk factors; IgA nephropathy; disease progression; prognosis; Kidney disease; IgA; Urinary system disease; Prognosis; Hemodialysis; Algorithm; Decision tree; Extrarenal dialysis; Nephropathy; Cohort study; Risk factor; Renal failure
• ISSN: 0931-0509; 1460-2385; 1460-2385
• DOI: 10.1093/ndt/gfn610

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.