Predicting long-term kidney allograft outcomes: pitfalls and progress

被引:2
作者
Dinh, Alex [1 ]
McCulloch, Charles E. [2 ]
Ku, Elaine [1 ,2 ,3 ]
机构
[1] Univ Calif San Francisco, Dept Med, Div Nephrol, 533 Parnassus Ave,U404,Box 0532, San Francisco, CA 94143 USA
[2] Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA USA
[3] Univ Calif San Francisco, Dept Pediat, Div Pediat Nephrol, San Francisco, CA USA
关键词
SURVIVAL;
D O I
10.1016/j.kint.2020.07.031
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Early identification of kidney transplant recipients at risk of progressive allograft dysfunction may allow clinicians to provide closer monitoring andmore aggressive risk factormodification. In this issue, Raynaud et al. presented a latent classmodel that clustered kidney transplant recipients into 8 risk categories of post-transplant kidney function loss. This commentary discusses some of the advantages, but also challenges, of the use of latent class analyses, including the clinical applicability of models that are often derived from such approaches. Copyright (C) 2020, International Society of Nephrology. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:24 / 26
页数:4
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