Diagnostic Accuracy Studies in Radiology: How to Recognize and Address Potential Sources of Bias
Author(s) -
Athanasios Pavlou,
Robert M. Kurtz,
Jae W. Song
Publication year - 2021
Publication title -
radiology research and practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.125
H-Index - 5
eISSN - 2090-1941
pISSN - 2090-195X
DOI - 10.1155/2021/5801662
Subject(s) - medicine , diagnostic accuracy , medical physics , diagnostic test , specialty , selection (genetic algorithm) , test (biology) , selection bias , radiology , medline , pathology , machine learning , computer science , pediatrics , paleontology , biology , political science , law
Accuracy is an important parameter of a diagnostic test. Studies that attempt to determine a test's accuracy can suffer from various forms of bias. As radiology is a diagnostic specialty, many radiologists may design a diagnostic accuracy study or review one to understand how it may apply to their practice. Radiologists also frequently serve as consultants to other physicians regarding the selection of the most appropriate diagnostic exams. In these roles, understanding how to critically appraise the literature is important for all radiologists. The purpose of this review is to provide a framework for evaluating potential sources of study design biases that are found in diagnostic accuracy studies and to explain their impact on sensitivity and specificity estimates. To help the reader understand these biases, we also present examples from the radiology literature.
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