Fundamental Statistical Concepts in Clinical Trials and Diagnostic Testing.
J Nucl Med
; 62(6): 757-764, 2021 06 01.
Article
em En
| MEDLINE
| ID: mdl-33608427
ABSTRACT
This article explores basic statistical concepts of clinical trial design and diagnostic testing, or how one starts with a question, formulates it into a hypothesis on which a clinical trial is then built, and integrates it with statistics and probability, such as determining the probability of rejecting the null hypothesis when it is actually true (type I error) and the probability of failing to reject the null hypothesis when it 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 type I error in the presence of multiple testing is needed to control the error's inflation. Within diagnostic testing, identifying false-positive and false-negative results is critical to understanding the performance of a test. These are used to determine the sensitivity and specificity of a test along with the test'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 to provide a basic understanding of clinical trial design and analysis, with references to allow the reader to explore various concepts at a more detailed level if desired.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Estatística como Assunto
/
Ensaios Clínicos como Assunto
/
Técnicas e Procedimentos Diagnósticos
Tipo de estudo:
Clinical_trials
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Diagnostic_studies
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Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
J Nucl Med
Ano de publicação:
2021
Tipo de documento:
Article