4.2 Article

Decision Analysis for the Evaluation of Diagnostic Tests, Prediction Models, and Molecular Markers

Journal

AMERICAN STATISTICIAN
Volume 62, Issue 4, Pages 314-320

Publisher

AMER STATISTICAL ASSOC
DOI: 10.1198/000313008X370302

Keywords

Decision support techniques; Outcome assessment; Prognosis

Funding

  1. National Cancer Institute [P50-CA92629]

Ask authors/readers for more resources

The traditional statistical approach to the evaluation of diagnostic tests, prediction models, and molecular markers is to assess their accuracy, using metrics such as sensitivity, specificity, and the receiver-operating-characteristic curve. However, there is no obvious association between accuracy and clinical value: it is unclear, for example, just how accurate a test needs to be in order for it to be considered accurate enough to warrant its use in patient care. Decision analysis aims to assess the clinical value of a test by assigning weights to each possible consequence. These methods have been historically considered unattractive to the practicing. biostatistician because additional data from the literature, or subjective assessments from individual patients or clinicians, are needed in order to assign weights appropriately. Decision analytic methods are available that can reduce these additional requirements. These methods can provide insight into the consequences of using a test, model, or marker in clinical practice.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.2
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available