Key concepts and limitations of statistical methods for evaluating biomarkers of kidney disease.
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.
Section of Nephrology, Yale University School of Medicine, Veterans Affairs Connecticut Healthcare System and the Program of Applied Translational Research, New Haven, Connecticut; and chirag.parikh@yale.edu.
Chirag R
CR
Parikh
Division of Nephrology, Department of Medicine, Western University, London, Ontario, Canada.
Heather
H
Thiessen-Philbrook
D019540:Area Under Curve; D015415:Biomarkers; D003661:Decision Support Techniques; D006801:Humans; D007674:Kidney Diseases / Q000175:diagnosis* / Q000209:etiology; D016017:Odds Ratio; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D012306:Risk
D015415:Biomarkers
NRI; biomarker; c index