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

Diagnostic and Prognostic Research

Ewout W. Steyerberg¹  Ben van Calster²  Andrew J. Vickers³ 

[1] Department of Biomedical Data Sciences, Leiden University Medical Center;Department of Development and Regeneration, KU Leuven;Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center;

关键词: Net benefit;    Decision curve analysis;    Educational paper;   

DOI  :  10.1186/s41512-019-0064-7

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown