Challenges in predictive modelling of chronic kidney disease:A narrative review

作     者：Sukhanshi Khandpur Prabhaker Mishra Shambhavi Mishra Swasti Tiwari 

作者机构：Department of Molecular Medicine&BiotechnologySanjay Gandhi Post Graduate Institute of Medical ScienceLucknow 226014Uttar PradeshIndia Department of Biostatistics and Health InformaticsSanjay Gandhi Post Graduate Institute of Medical SciencesLucknow 226014Uttar PradeshIndia Department of StatisticsUniversity of LucknowLucknow 226007Uttar PradeshIndia 

出 版 物：《World Journal of Nephrology》 (世界肾病学杂志（英文版）)

年 卷 期：2024年第13卷第3期

页      面：26-33页

学科分类：1002[医学-临床医学] 100210[医学-外科学(含：普外、骨外、泌尿外、胸心外、神外、整形、烧伤、野战外)] 10[医学] 

基　　金：Supported by Coord/7(1)/CAREKD/2018/NCD-II,No.5/4/7-12/13/NCD-II Senior Research Fellowship by the Indian Council of Medical Research,New Delhi,No.3/1/2(6)/Nephro/2022-NCD-II 

主　　题：Chronic kidney disease Predictive modelling Regression Statistical modelling Methodology 

摘      要：The exponential rise in the burden of chronic kidney disease(CKD)worldwide has put enormous pressure on the *** modeling of CKD can ease this burden by predicting the future disease occurrence ahead of its *** are various regression methods for predictive modeling based on the distribution of the outcome ***,the accuracy of the predictive model depends on how well the model is developed by taking into account the goodness of fit,choice of covariates,handling of covariates measured on a continuous scale,handling of categorical covariates,and number of outcome events per predictor parameter or sample *** performance of a predictive model on an independent cohort is ***,there are several challenges in the predictive modeling of ***-specific methodological challenges hinder the development of a predictive model that is cost-effective and universally applicable to predict CKD *** this review,we discuss the advantages and challenges of various regression models available for predictive modeling and highlight those best for future CKD prediction.