Cited by 594Statistical Methods in EpidemiologyMeta-analysis and systematic reviewsAdvanced Causal Inference Techniques

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Net Reclassification Improvement: Computation, Interpretation, and Controversies: A Literature Review and Clinician's Guide

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Leening, Maarten J.G., Vedder, Moniek M., Witteman, Jacqueline C.M., Pencina, Michael J., Steyerberg, Ewout W.·2014·Annals of Internal Medicine

DOI 10.7326/m13-1522

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Abstract

The net reclassification improvement (NRI) is an increasingly popular measure for evaluating improvements in risk predictions. This article details a review of 67 publications in high-impact general clinical journals that considered the NRI. Incomplete reporting of NRI methods, incorrect calculation, and common misinterpretations were found. To aid improved applications of the NRI, the article elaborates on several aspects of the computation and interpretation in various settings. Limitations and controversies are discussed, including the effect of miscalibration of prediction models, the use of the continuous NRI and “clinical NRI,” and the relation with decision analytic measures. A systematic approach toward presenting NRI analysis is proposed: Detail and motivate the methods used for computation of the NRI, use clinically meaningful risk cutoffs for the category-based NRI, report both NRI components, address issues of calibration, and do not interpret the overall NRI as a percentage of the study population reclassified. Promising NRI findings need to be followed with decision analytic or formal cost-effectiveness evaluations.

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Authors: Leening, M. J. G., Vedder, M. M., Witteman, J. C. M., Pencina, M. J., & Steyerberg, E. W.
Affiliations: Duke University (US)
ORCID: Leening, Maarten J.G.
Pencina, Michael J.
Steyerberg, Ewout W.
Venue: Annals of Internal Medicine
Publisher: American College of Physicians
Published: 2014-01-21
Volume: 160
Issue: 2
Pages: 122-131
ISSN: 0003-4819 (ISSN-L)
1539-3704
DOI: 10.7326/m13-1522
OpenAlex: W2103645914
Cited by: 594
References: 141
Citations by year: 2026: 38 · 2025: 30 · 2024: 41 · 2023: 59 · 2022: 59 · 2021: 53 · 2020: 56 · 2019: 39 · 2018: 49 · 2017: 44 · 2016: 55 · 2015: 47 · 2014: 23
FWCI: 7.11
Type: journal article
Language: en
Open access: green
hdl.handle.net
Licence: other-oa
www.acpjournals.org/journal/aim/text-and-data-mining (tdm)
Locations: Annals of Internal Medicine (publishedVersion)
PubMed (publishedVersion)
EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords: net reclassification improvement, risk prediction model, model calibration, cost-effectiveness, reporting quality
MeSH terms: Data Interpretation, Statistical, Decision Support Techniques, Humans, Models, Statistical, Risk Assessment

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Net Reclassification Improvement: Computation, Interpretation, and Controversies: A Literature Review and Clinician's Guide

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