Different View Of The Diagnostics Test Accuracy Measures And Optimal Cut-off Point Selection Procedure Under Tree Or Umbrella Ordering

Authors

Jing Kersey, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Hani Samawi, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Marwan Alsharman, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Mario Keko, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Haresh Rochani, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Lili Yu, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Jingjing Yin, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Kelly L. Sullivan, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Salaheddin Mustafa, University of Jordan

Document Type

Article

Publication Date

10-30-2024

Publication Title

Journal of Biopharmaceutical Statistics

DOI

10.1080/10543406.2024.2420659

Abstract

In the realm of medical diagnostic testing, diagnostic tests can assume either binary forms, distinguishing between diseased and non-diseased states, or ordinal forms, categorizing states from non-diseased to various stages (1 to K). Another significant classification scheme for multi-class scenarios is tree or umbrella ordering, which entails several unordered sub-classes (subtypes) within a biomarker. Within tree or umbrella ordering, the classifier assesses whether the marker measurement for one class surpasses or falls below those for the other classes. Although Receiver Operating Characteristic (ROC) curves and summary measures have been adapted to accommodate tree and umbrella ordering, these approaches often yield cut-off points that generate highly sensitive tests for certain disease subtypes while compromising specificity for others. This may not be ideal for all diseases. Hence, in this investigation, we explore diverse measures of diagnostic test accuracy and optimal cut-off point selection procedures under tree or umbrella ordering to foster more specific tests. We present numerical examples and simulation studies and demonstrate the approach using real data on lung cancer.

Comments

Georgia Southern University faculty member, Jing Kersey, Hani Samawi, Mario Keko, Haresh Rochani, Lili Yu, Jingjing Yin, and Kelly Sullivan co-authored, Different View Of The Diagnostics Test Accuracy Measures And Optimal Cut-off Point Selection Procedure Under Tree Or Umbrella Ordering.

Recommended Citation

Kersey, Jing, Hani Samawi, Marwan Alsharman, Mario Keko, Haresh Rochani, Lili Yu, Jingjing Yin, Kelly L. Sullivan, Salaheddin Mustafa. 2024. "Different View Of The Diagnostics Test Accuracy Measures And Optimal Cut-off Point Selection Procedure Under Tree Or Umbrella Ordering." Journal of Biopharmaceutical Statistics: Taylor and Francis Online. doi: 10.1080/10543406.2024.2420659
https://digitalcommons.georgiasouthern.edu/bee-facpubs/418

Copyright

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