Using Decision Curve Analysis to Evaluate Testing and/or Predictive Modeling

Benjamin Djulbegovic; Iztok Hozo

doi:10.1007/978-3-031-37993-2_6

Using Decision Curve Analysis to Evaluate Testing and/or Predictive Modeling

Cancer Treat Res. 2023:189:77-84. doi: 10.1007/978-3-031-37993-2_6.

Authors

Benjamin Djulbegovic¹, Iztok Hozo²

Affiliations

¹ Hematology Stewardship Program, Division of Hematology/Oncology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA. [email protected].
² Department of Mathematics, Indiana University Northwest, Gary, IN, USA.

PMID: 37789162
DOI: 10.1007/978-3-031-37993-2_6

Abstract

In this chapter, we extend the threshold model to evaluate the value of diagnostic tests or predictive models over a range of all possible thresholds by using decision curve analysis (DCA). DCA has been developed within the expected utility theory (EUT) and expected regret theory (ERT) framework.

MeSH terms

Decision Support Techniques*
Diagnostic Techniques and Procedures*
Humans