Key Concepts and Limitations of Statistical Methods for Evaluating Biomarkers of Kidney Disease

被引：44

作者：

Parikh, Chirag R. ^{[1
,2
]}

Thiessen-Philbrook, Heather ^{[3
]}

机构：

[1] Yale Univ, Sch Med, Nephrol Sect, Vet Affairs Connecticut Healthcare Syst, New Haven, CT 06510 USA

[2] Program Appl Translat Res, New Haven, CT USA

[3] Univ Western Ontario, Dept Med, Div Nephrol, London, ON, Canada

来源：

JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY | 2014年 / 25卷 / 08期

基金：

美国国家卫生研究院;

关键词：

RISK-PREDICTION-MODELS; NET RECLASSIFICATION; INCREMENTAL VALUE; NESTED MODELS; PERFORMANCE; MARKERS; IMPROVEMENT; INJURY; STANDARDS; DIAGNOSIS;

D O I：

10.1681/ASN.2013121300

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：

Interest in developing and using novel markers of kidney injury is increasing. To maintain scientific rigour in these endeavors, a comprehensive understanding of statistical methodology is required to rigorously assess the incremental value of novel biomarkers in existing clinical risk prediction models. Such knowledge is especially relevant, because no single statistical method is sufficient to evaluate a novel biomarker. In this review, we highlight the strengths and limitations of various traditional and novel statistical methods used in the literature for biomarker studies and use biomarkers of AKI as examples to show limitations of some popular statistical methods.

引用

页码：1621 / 1629

页数：9

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