Molecular imaging technologists are faced with statistics on a daily basis because they image patients who have been selected for diagnostic testing based on analysis of how well the test performs, and because technical factors can influence the performance of any diagnostic test. Choosing what test procedure to perform on which patient is a matter of understanding the patient's pretest likelihood of disease, the performance characteristics of the diagnostic test, and other clinical factors which may impact the usefulness of the results. Terms such as sensitivity, specificity, accuracy, and predictive value are used to describe how a diagnostic test performs, or how it compares to other diagnostic tests. While nuclear medicine and PET technologists study these concepts in training programs, applying this learning to daily patient care can be daunting given that new tracers and technologies are continuously moving into clinical practice. Research advances continue to challenge diagnostic paradigms with new patient populations, increasingly sophisticated technology, and the advent of large databases with which to study population outcomes. This article is part I of a two-part series. The purpose of this article is to provide a refresher about basic clinical statistics that are useful in understanding how diagnostic testing is optimally applied in the patient care setting.
Keywords: Molecular Imaging; Quality Assurance; Sensitivity; Specificity; Statistical Analysis; Statistics.
Copyright © 2017 by the Society of Nuclear Medicine and Molecular Imaging, Inc.