Jingyuan Xie1, Jicheng Lv2, Weiming Wang3, Guisen Li4, Zhangsuo Liu5, Hongyu Chen6, Feifei Xu7, Jing Sun8, Yan Ouyang3, Xiaoyan Zhang3, Meng Yang3, Manman Shi3, Wen Zhang3, Hong Ren3, Krzysztof Kiryluk9, Hong Zhang2, Nan Chen10. 1. Institute of Nephrology, Department of Nephrology, Shanghai Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China. Electronic address: nephroxie@163.com. 2. Renal Division, Department of Medicine, Peking University First Hospital, Beijing, China. 3. Institute of Nephrology, Department of Nephrology, Shanghai Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China. 4. Department of Nephrology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China. 5. Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China. 6. Department of Nephrology, Hangzhou Hospital of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China. 7. Department of Nephrology, the First Affiliated Hospital of Wenzhou Medical College, Wenzhou, China. 8. Renal Division, The 455 Hospital of Chinese People's Liberation Army, Shanghai, China. 9. Division of Nephrology, Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY. 10. Institute of Nephrology, Department of Nephrology, Shanghai Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China. Electronic address: cnrj100@126.com.
Abstract
BACKGROUND: The clinical course of immunoglobulin A (IgA) nephropathy (IgAN) is highly variable, making it difficult to predict which patients are at risk for rapid progression. The aim of this study was to develop and validate a kidney failure risk prediction equation for adults with IgAN. STUDY DESIGN: Multicenter retrospective cohort study of 2,155 Chinese patients with IgAN. CANDIDATE PREDICTORS: Clinical and histology variables. OUTCOMES: Time to end-stage renal disease (ESRD). ANALYTICAL APPROACH: The association of baseline predictors with the outcome was tested using cause-specific hazards models by treating death as a censoring event. RESULTS: The discovery cohort was composed of 934 IgAN cases with a mean follow-up of 56.3 months. The independent validation cohort was composed of 1,221 additional patients with a mean follow-up of 47.8 months. There were 212 ESRD events in the combined cohort. The best clinical predictive model of ESRD included 5 variables: age, sex, estimated glomerular filtration rate, hemoglobin concentration, and urine protein excretion. The best model combining clinical and histologic data included 2 clinical variables (age and estimated glomerular filtration rate) and 2 pathology scores (M and T scores from the Oxford classification). Both models predicted ESRD well at 10 years in the validation cohort (C statistics of 0.86 [95% CI, 0.83-0.90] and 0.83 [95% CI, 0.77-0.89], respectively). Continuous net reclassification index and integrated discrimination improvement indicated superior performance of the new models compared with previously published models. The performance of the new clinical model was similar to that of the new model that incorporated histologic variables. LIMITATIONS: Retrospective study design, differences in severity of disease between the discovery and validation cohorts, the competing risk of death, lack of validation in ethnically diverse patients. CONCLUSIONS: Kidney failure risk in the setting of IgAN is able to be predicted in a Chinese population using clinical and histologic variables. Additional evaluation of these equations needs to be implemented in more ethnically diverse patients before they can be applied to clinical practice broadly.
BACKGROUND: The clinical course of immunoglobulin A (IgA) nephropathy (IgAN) is highly variable, making it difficult to predict which patients are at risk for rapid progression. The aim of this study was to develop and validate a kidney failure risk prediction equation for adults with IgAN. STUDY DESIGN: Multicenter retrospective cohort study of 2,155 Chinese patients with IgAN. CANDIDATE PREDICTORS: Clinical and histology variables. OUTCOMES: Time to end-stage renal disease (ESRD). ANALYTICAL APPROACH: The association of baseline predictors with the outcome was tested using cause-specific hazards models by treating death as a censoring event. RESULTS: The discovery cohort was composed of 934 IgAN cases with a mean follow-up of 56.3 months. The independent validation cohort was composed of 1,221 additional patients with a mean follow-up of 47.8 months. There were 212 ESRD events in the combined cohort. The best clinical predictive model of ESRD included 5 variables: age, sex, estimated glomerular filtration rate, hemoglobin concentration, and urine protein excretion. The best model combining clinical and histologic data included 2 clinical variables (age and estimated glomerular filtration rate) and 2 pathology scores (M and T scores from the Oxford classification). Both models predicted ESRD well at 10 years in the validation cohort (C statistics of 0.86 [95% CI, 0.83-0.90] and 0.83 [95% CI, 0.77-0.89], respectively). Continuous net reclassification index and integrated discrimination improvement indicated superior performance of the new models compared with previously published models. The performance of the new clinical model was similar to that of the new model that incorporated histologic variables. LIMITATIONS: Retrospective study design, differences in severity of disease between the discovery and validation cohorts, the competing risk of death, lack of validation in ethnically diverse patients. CONCLUSIONS:Kidney failure risk in the setting of IgAN is able to be predicted in a Chinese population using clinical and histologic variables. Additional evaluation of these equations needs to be implemented in more ethnically diverse patients before they can be applied to clinical practice broadly.