Literature DB >> 24403241

Value of information methods for assessing a new diagnostic test.

Maggie Hong Chen1, Andrew R Willan.   

Abstract

Value-of-information methods are applied to assess the evidence in support of a new diagnostic test and, where the evidence is insufficient for decision making, to determine the optimal sample size for future studies. Net benefit formulations are derived under various diagnostic and treatment scenarios. The expressions for the expected opportunity loss of adopting strategies that include the new test are given. Expressions for the expected value of information from future studies are derived. One-sample and two-sample designs, with or without known prevalence, are considered. An example is given.
Copyright © 2014 John Wiley & Sons, Ltd.

Keywords:  diagnostic tests; full Bayesian approach, incremental net benefit; value of information

Mesh:

Year:  2014        PMID: 24403241     DOI: 10.1002/sim.6085

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  2 in total

1.  A simple framework to identify optimal cost-effective risk thresholds for a single screen: Comparison to Decision Curve Analysis.

Authors:  Hormuzd A Katki; Ionut Bebu
Journal:  J R Stat Soc Ser A Stat Soc       Date:  2021-03-23       Impact factor: 2.175

2.  How to interpret a small increase in AUC with an additional risk prediction marker: decision analysis comes through.

Authors:  Stuart G Baker; Ewoud Schuit; Ewout W Steyerberg; Michael J Pencina; Andrew Vickers; Andew Vickers; Karel G M Moons; Ben W J Mol; Karen S Lindeman
Journal:  Stat Med       Date:  2014-05-13       Impact factor: 2.373

  2 in total

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