Literature DB >> 19124107

Reducing the number of reader interpretations in MRMC studies.

Nancy A Obuchowski1.   

Abstract

RATIONALE AND
OBJECTIVES: Multireader, multicase (MRMC) receiver-operating characteristic studies often require large numbers of patients, readers, and reader interpretations. The objective of this work is to evaluate a new "mixed" MRMC study design that reduces the number of reader interpretations.
MATERIALS AND METHODS: As compared to the traditional MRMC design, the number of reader interpretations and the number of cases that must be truth-verified for the new mixed design was evaluated theoretically and empirically for various correlation values and sample sizes.
RESULTS: For large MRMC studies, the new mixed design offers a substantial savings in the number of reader interpretations if the magnitude of the difference in between-reader correlations is not zero. For example, compared to a traditional design with 20 readers, 200 total cases, and a difference in between-reader correlations of 0.05, the newly proposed mixed design requires each reader to interpret only 132 cases, but at a cost of truth-verifying an additional 64 cases.
CONCLUSIONS: The mixed design can reduce the number of cases that readers need to interpret and the overall duration of a study, but at a cost in terms of the number of cases that must be truth-verified. The mixed design is particularly useful for studies where the condition being detected is not rare and patients routinely undergo the gold standard assessment.

Entities:  

Mesh:

Year:  2009        PMID: 19124107     DOI: 10.1016/j.acra.2008.05.014

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  12 in total

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8.  Relationship between Roe and Metz simulation model for multireader diagnostic data and Obuchowski-Rockette model parameters.

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Journal:  Stat Med       Date:  2018-04-02       Impact factor: 2.373

9.  A marginal-mean ANOVA approach for analyzing multireader multicase radiological imaging data.

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