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A note on the evaluation of novel biomarkers

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Authors:
  • Hilden, Jørgen ;
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    Section of Biostatistics, Department of Public Health, Faculty of Health and Medical Sciences, Københavns Universitet
  • Gerds, Thomas A
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    Section of Biostatistics, Department of Public Health, Faculty of Health and Medical Sciences, Københavns Universitet
Subtitle:
do not rely on integrated discrimination improvement and net reclassification index
DOI:
10.1002/sim.5804
Abstract:
The 'integrated discrimination improvement' (IDI) and the 'net reclassification index' (NRI) are statistics proposed as measures of the incremental prognostic impact that a new biomarker will have when added to an existing prediction model for a binary outcome. By design, both measures were meant to be intuitively appropriate, and the IDI and NRI formulae do look intuitively plausible. Both have become increasingly popular. We shall argue, however, that their use is not always safe. If IDI and NRI are used to measure gain in prediction performance, then poorly calibrated models may appear advantageous, and in a simulation study, even the model that actually generates the data (and hence is the best possible model) can be improved on without adding measured information. We illustrate these shortcomings in actual cancer data as well as by Monte Carlo simulations. In these examples, we contrast IDI and NRI with the area under ROC and the Brier score. Unlike IDI and NRI, these traditional measures have the characteristic that prognostic performance cannot be accidentally or deliberately inflated.
Type:
Journal article
Language:
English
Published in:
Statistics in Medicine, 2014, Vol 33, Issue 19, p. 3405-14
Main Research Area:
Medical science
Publication Status:
Published
Review type:
Peer Review
Submission year:
2014
Scientific Level:
Scientific
ID:
247287854

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