Expected utility versus expected regret theory versions of decision curve analysis do generate different results when treatment effects are taken into account.

ABSTRACT:

Rationale, aims, and objectives

Decision curve analysis (DCA) is a widely used method for evaluating diagnostic tests and predictive models. It was developed based on expected utility theory (EUT) and has been reformulated using expected regret theory (ERG). Under certain circumstances, these 2 formulations yield different results. Here we describe these situations and explain the variation.

Methods

We compare the derivations of the EUT- and ERG-based formulations of DCA for a typical medical decision problem: "treat none," "treat all," or "use model" to guide treatment. We illustrate the differences between the 2 formulations when applied to the following clinical question: at which probability of death we should refer a terminally ill patient to hospice?

Results

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SUBMITTER: Hozo I 

PROVIDER: S-EPMC5900988 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature