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Threshold-Free Measures for Assessing the Performance of Medical Screening Tests

Overview of attention for article published in Frontiers in Public Health, April 2015
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Title
Threshold-Free Measures for Assessing the Performance of Medical Screening Tests
Published in
Frontiers in Public Health, April 2015
DOI 10.3389/fpubh.2015.00057
Pubmed ID
Authors

Yan Yuan, Wanhua Su, Mu Zhu

Abstract

The area under the receiver operating characteristic curve (AUC) is frequently used as a performance measure for medical tests. It is a threshold-free measure that is independent of the disease prevalence rate. We evaluate the utility of the AUC against an alternate measure called the average positive predictive value (AP), in the setting of many medical screening programs where the disease has a low prevalence rate. We define the two measures using a common notation system and show that both measures can be expressed as a weighted average of the density function of the diseased subjects. The weights for the AP include prevalence in some form, but those for the AUC do not. These measures are compared using two screening test examples under rare and common disease prevalence rates. The AP measures the predictive power of a test, which varies when the prevalence rate changes, unlike the AUC, which is prevalence independent. The relationship between the AP and the prevalence rate depends on the underlying screening/diagnostic test. Therefore, the AP provides relevant information to clinical researchers and regulators about how a test is likely to perform in a screening population. The AP is an attractive alternative to the AUC for the evaluation and comparison of medical screening tests. It could improve the effectiveness of screening programs during the planning stage.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 35%
Researcher 5 16%
Student > Master 4 13%
Student > Doctoral Student 3 10%
Student > Bachelor 2 6%
Other 3 10%
Unknown 3 10%
Readers by discipline Count As %
Computer Science 6 19%
Biochemistry, Genetics and Molecular Biology 4 13%
Mathematics 3 10%
Agricultural and Biological Sciences 3 10%
Physics and Astronomy 2 6%
Other 7 23%
Unknown 6 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 April 2015.
All research outputs
#18,407,102
of 22,800,560 outputs
Outputs from Frontiers in Public Health
#5,662
of 9,798 outputs
Outputs of similar age
#193,192
of 264,968 outputs
Outputs of similar age from Frontiers in Public Health
#48
of 72 outputs
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