Developing Risk Prediction Models for Kidney Injury and Assessing Incremental Value for Novel Biomarkers | Zendy

Kathleen F. Kerr | Zendy; Allison Meisner | Zendy; Heather ThiessenPhilbrook | Zendy; Steven G. Coca | Zendy; Chirag R. Parikh | Zendy

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Developing Risk Prediction Models for Kidney Injury and Assessing Incremental Value for Novel Biomarkers

Author(s) -

Kathleen F. Kerr,

Allison Meisner,

Heather ThiessenPhilbrook,

Steven G. Coca,

Chirag R. Parikh

Publication year - 2014

Publication title -

clinical journal of the american society of nephrology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.755

H-Index - 151

eISSN - 1555-905X

pISSN - 1555-9041

DOI - 10.2215/cjn.10351013

Subject(s) - medicine , biomarker , intensive care medicine , predictive value , acute kidney injury , risk assessment , nephrology , predictive modelling , value (mathematics) , risk analysis (engineering) , machine learning , computer science , biochemistry , chemistry , computer security

The field of nephrology is actively involved in developing biomarkers and improving models for predicting patients' risks of AKI and CKD and their outcomes. However, some important aspects of evaluating biomarkers and risk models are not widely appreciated, and statistical methods are still evolving. This review describes some of the most important statistical concepts for this area of research and identifies common pitfalls. Particular attention is paid to metrics proposed within the last 5 years for quantifying the incremental predictive value of a new biomarker.

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