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. 2019 Oct 4:3:18.
doi: 10.1186/s41512-019-0064-7. eCollection 2019.

A simple, step-by-step guide to interpreting decision curve analysis

Andrew J Vickers  1 , Ben van Calster  2   3 , Ewout W Steyerberg  3
Affiliations

A simple, step-by-step guide to interpreting decision curve analysis

Andrew J Vickers et al. Diagn Progn Res. .

Abstract

Background: Decision curve analysis is a method to evaluate prediction models and diagnostic tests that was introduced in a 2006 publication. Decision curves are now commonly reported in the literature, but there remains widespread misunderstanding of and confusion about what they mean.

Summary of commentary: In this paper, we present a didactic, step-by-step introduction to interpreting a decision curve analysis and answer some common questions about the method. We argue that many of the difficulties with interpreting decision curves can be solved by relabeling the y-axis as "benefit" and the x-axis as "preference." A model or test can be recommended for clinical use if it has the highest level of benefit across a range of clinically reasonable preferences.

Conclusion: Decision curves are readily interpretable if readers and authors follow a few simple guidelines.

Keywords: Decision curve analysis; Educational paper; Net benefit.

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Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
A decision curve plotting benefit against preference
Fig. 2
Fig. 2
A decision curve plotting net benefit against threshold probability
Fig. 3
Fig. 3
A decision curve plotting decrease in interventions against threshold probability
See this image and copyright information in PMC

Comment in

References

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