@article {Pughjnumed.120.245654,
author = {Pugh, Stephanie L. and Torres-Saavedra, Pedro},
title = {Fundamental Statistical Concepts in Clinical Trials and Diagnostic Testing},
elocation-id = {jnumed.120.245654},
year = {2021},
doi = {10.2967/jnumed.120.245654},
publisher = {Society of Nuclear Medicine},
abstract = {This article explores basic statistical concepts of clinical trial design and diagnostic testing. How one starts with a question, formulates it into a hypothesis upon which a clinical trial is then built, is integrated with statistics and probability, such as determining the probability of rejecting the null hypothesis when its actually true (type I error) and the probability of failing to reject the null hypothesis when the null hypothesis is false (type II error). There are a variety of tests for different types of data and the appropriate test must be chosen for which the sample data meet the assumptions. Correcting of the type I error in the presence of multiple testing is needed to control the error{\textquoteright}s inflation. Within diagnostic testing, identifying false positive and false negative patients is critical to understanding the performance of a test. These are utilized to determine the sensitivity and specificity of a test along with the test{\textquoteright}s negative predictive value and positive predictive value. These quantities, specifically sensitivity and specificity, are used to determine the accuracy of a diagnostic test using receiver operating characteristic curves. These concepts are briefly introduced, with references to allow the reader to explore various concepts at a more detailed level if desired, to provide a basic understanding of clinical trial design and analysis.},
issn = {0161-5505},
URL = {https://jnm.snmjournals.org/content/early/2021/02/19/jnumed.120.245654},
eprint = {https://jnm.snmjournals.org/content/early/2021/02/19/jnumed.120.245654.full.pdf},
journal = {Journal of Nuclear Medicine}
}