Clinical decision support system for end-stage kidney disease risk estimation in IgA nephropathy patients

Zhang

et al. 2018

Kidney Blood Press Res

Background/Aims: There is an increasing risk of end-stage renal disease (ESRD) among Asian people with immunoglobulin A nephropathy (IgAN). A computer-aided system for ESRD prediction in Asian IgAN patients has not been well studied. Methods: We retrospectively reviewed biopsy-proven IgAN patients treated at the Department of Nephrology of the Second Xiangya Hospital from January 2009 to November 2013. Demographic and clinicopathological data were obtained within 1 month of renal biopsy. A random forest (RF) model was employed to predict the ESRD status in IgAN patients. All cases were initially trained and validated, taking advantage of the out-of-bagging(OOB) error. Predictors used in the model were selected according to the Gini impurity index in the RF model and verified by logistic regression analysis. The area under the receiver operating characteristic(ROC) curve (AUC) and F-measure were used to evaluate the RF model. Results: A total of 262 IgAN patients were enrolled in this study with a median follow-up time of 4.66 years. The importance rankings of predictors of ESRD in the RF model were first obtained, indicating some of the most important predictors. Logistic regression also showed that these factors were statistically associated with ESRD status. We first trained an initial RF model using gender, age, hypertension, serum creatinine, 24-hour proteinuria and histological grading suggested by the Clinical Decision Support System for IgAN (CDSS, www.IgAN.net). This 6-predictor model achieved a F-measure of 0.8 and an AUC of 92.57%. By adding Oxford-MEST scores, this model outperformed the initial model with an improved AUC (96.1%) and F-measure (0.823). When C3 staining was incorporated, the AUC was 97.29% and F-measure increased to 0.83. Adding the estimated glomerular filtration rate (eGFR) improved the AUC to 95.45%. We also observed improved performance of the model with additional inputs of blood urea nitrogen (BUN), uric acid, hemoglobin and albumin. Conclusion: In addition to the predictors in the CDSS, Oxford-MEST scores, C3 staining and eGFR conveyed additional information for ESRD prediction in Chinese IgAN patients using a RF model.

Section: Evaluation Of Clinicopathological Parametersmentioning

confidence: 99%

Section: Clinical and Pathological Characteristics Of The Populationmentioning

confidence: 99%

Section: Performance Of the Rf Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prediction of ESRD in IgA Nephropathy Patients from an Asian Cohort: A Random Forest Model

Zhang

et al. 2018

Kidney Blood Press Res

“…The prevalence of IgAN shows marked differences across different ethnic groups, being more prevalent in people with East Asian ancestry and less prevalent in people with African ancestry compared with Caucasians 2 . In addition, differences in the clinical features of IgAN in Caucasian compared with Chinese patients have been recognized for a long time 3 , most notably the clear male preponderance of IgAN in Caucasian studies of IgAN that is absent (or even reversed) in East Asian populations, suggesting that important and incompletely understood differences in disease pathophysiology exist across different populations [4][5][6][7][8] . Recent work has identified a number of genetic factors, mostly associated with mechanisms of defense against infection, that are associated with altered risk of disease [9][10][11] , and although the prevalence of the known genetic factors vary across different ethnic groups, the observed differences fall some way short of explaining the differences in prevalence of the disease in different regions 2,12 .…”

Section: Introductionmentioning

confidence: 99%

Galactosylation of IgA1 Is Associated with Common Variation in C1GALT1

Gale

Molyneux

Wimbury

et al. 2017

JASN

112

IgA nephropathy (IgAN), an important cause of kidney failure, is characterized by glomerular IgA deposition and is associated with changes in O-glycosylation of the IgA1 molecule. Here, we sought to identify genetic factors contributing to levels of galactose-deficient IgA1 (Gd-IgA1) in Caucasian and Chinese populations.Gd-IgA1 levels were elevated in IgAN patients compared with ethnically matched healthy subjects and correlated with evidence of disease progression. Caucasian IgAN patients exhibited significantly higher Gd-IgA1 levels than Chinese patients. Among individuals without IgAN, Gd-IgA1 levels were not correlated with kidney function. Gd-IgA1 level heritability (h ). This association was replicated in GWAS of separate cohorts comprising: 308 UK patients with membranous glomerulonephritis (p<10

Evaluating a New International Risk-Prediction Tool in IgA Nephropathy

et al. 2019

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 R 2 D 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 R 2 D (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 R 2 D (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.