A calibration hierarchy for risk models was defined: from utopia to empirical data.

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Abstract

Calibrated risk models are vital for valid decision support. We define four levels of calibration and describe implications for model development and external validation of predictions.

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Journal

Journal ID (iso-abbrev): J Clin Epidemiol

Title: Journal of clinical epidemiology

Publisher: Elsevier BV

ISSN (Electronic): 1878-5921

ISSN (Print): 0895-4356

Publication date (Electronic): Jun 2016

Volume: 74

Affiliations

[1 ] KU Leuven, Department of Development and Regeneration, Herestraat 49 Box 7003, 3000 Leuven, Belgium; Department of Public Health, Erasmus MC, 's-Gravendijkwal 230, 3015 CE Rotterdam, The Netherlands. Electronic address: ben.vancalster@med.kuleuven.be.

[2 ] Department of Public Health, Erasmus MC, 's-Gravendijkwal 230, 3015 CE Rotterdam, The Netherlands.

[3 ] KU Leuven, Department of Development and Regeneration, Herestraat 49 Box 7003, 3000 Leuven, Belgium.

[4 ] Duke Clinical Research Institute, Duke University, 2400 Pratt Street, Durham, NC 27705, USA; Department of Biostatistics and Bioinformatics, Duke University, 2424 Erwin Road, Durham, NC 27719, USA.

Article

Publisher Item ID: S0895-4356(15)00581-8

DOI: 10.1016/j.jclinepi.2015.12.005

PubMed ID: 26772608

SO-VID: ff47587b-cd0d-4c66-8f1c-d52c3503c106

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Keywords: Calibration,Decision curve analysis,External validation,Loess,Overfitting,Risk prediction models

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Keywords: Calibration, Decision curve analysis, External validation, Loess, Overfitting, Risk prediction models

A calibration hierarchy for risk models was defined: from utopia to empirical data.

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