An easy-to-operate web-based calculator for predicting the progression of chronic kidney disease

Journal of Translational Medicine

Yunyun Wang¹  Shanshan Feng²  Yanxia Jiang²  Cuiyun Chen²  Yiqun Fang³  Qian Xu⁴ 

[1]Academic Affairs Office, First Affiliated Hospital of Nanchang University, 330006, Nanchang, Jiangxi, China

[2]Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanchang University, 17 Yongwai, 330006, Nanchang, Jiangxi, People’s Republic of China

[3]Department of Endocrinology and Metabolism, Jingdezhen First People’s Hospital, 333000, Jingdezhen, Jiangxi, China

[4]Health Management Center, First Affiliated Hospital of Nanchang University, 330006, Nanchang, Jiangxi, China

关键词: Chronic kidney disease;    End-stage renal disease;    Area under the curve;    Prognostic factor;    Progression-free survival;   

DOI  :  10.1186/s12967-021-02942-y

来源: Springer

【 摘 要 】

BackgroundThis study aimed to establish and validate an easy-to-operate novel scoring system based on simple and readily available clinical indices for predicting the progression of chronic kidney disease (CKD).MethodsWe retrospectively evaluated 1045 eligible CKD patients from a publicly available database. Factors included in the model were determined by univariate and multiple Cox proportional hazard analyses based on the training set.ResultsIndependent prognostic factors including etiology, hemoglobin level, creatinine level, proteinuria, and urinary protein/creatinine ratio were determined and contained in the model. The model showed good calibration and discrimination. The area under the curve (AUC) values generated to predict 1-, 2-, and 3-year progression-free survival in the training set were 0.947, 0.931, and 0.939, respectively. In the validation set, the model still revealed excellent calibration and discrimination, and the AUC values generated to predict 1-, 2-, and 3-year progression-free survival were 0.948, 0.933, and 0.915, respectively. In addition, decision curve analysis demonstrated that the model was clinically beneficial. Moreover, to visualize the prediction results, we established a web-based calculator (https://ncutool.shinyapps.io/CKDprogression/).ConclusionAn easy-to-operate model based on five relevant factors was developed and validated as a conventional tool to assist doctors with clinical decision-making and personalized treatment.

【 授权许可】

CC BY