Cargando…
Informative noncompliance in endpoint trials
Noncompliance with study medications is an important issue in the design of endpoint clinical trials. Including noncompliant patient data in an intention-to-treat analysis could seriously decrease study power. Standard methods for calculating sample size account for noncompliance, but all assume tha...
Autores principales: | , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2004
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC469444/ https://www.ncbi.nlm.nih.gov/pubmed/15233844 http://dx.doi.org/10.1186/1468-6708-5-5 |
_version_ | 1782121626153779200 |
---|---|
author | Snapinn, Steven M Jiang, Qi Iglewicz, Boris |
author_facet | Snapinn, Steven M Jiang, Qi Iglewicz, Boris |
author_sort | Snapinn, Steven M |
collection | PubMed |
description | Noncompliance with study medications is an important issue in the design of endpoint clinical trials. Including noncompliant patient data in an intention-to-treat analysis could seriously decrease study power. Standard methods for calculating sample size account for noncompliance, but all assume that noncompliance is noninformative, i.e., that the risk of discontinuation is independent of the risk of experiencing a study endpoint. Using data from several published clinical trials (OPTIMAAL, LIFE, RENAAL, SOLVD-Prevention and SOLVD-Treatment), we demonstrate that this assumption is often untrue, and we discuss the effect of informative noncompliance on power and sample size. |
format | Text |
id | pubmed-469444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-4694442004-07-16 Informative noncompliance in endpoint trials Snapinn, Steven M Jiang, Qi Iglewicz, Boris Curr Control Trials Cardiovasc Med Review Noncompliance with study medications is an important issue in the design of endpoint clinical trials. Including noncompliant patient data in an intention-to-treat analysis could seriously decrease study power. Standard methods for calculating sample size account for noncompliance, but all assume that noncompliance is noninformative, i.e., that the risk of discontinuation is independent of the risk of experiencing a study endpoint. Using data from several published clinical trials (OPTIMAAL, LIFE, RENAAL, SOLVD-Prevention and SOLVD-Treatment), we demonstrate that this assumption is often untrue, and we discuss the effect of informative noncompliance on power and sample size. BioMed Central 2004 2004-07-03 /pmc/articles/PMC469444/ /pubmed/15233844 http://dx.doi.org/10.1186/1468-6708-5-5 Text en Copyright © 2004 Snapinn et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL. |
spellingShingle | Review Snapinn, Steven M Jiang, Qi Iglewicz, Boris Informative noncompliance in endpoint trials |
title | Informative noncompliance in endpoint trials |
title_full | Informative noncompliance in endpoint trials |
title_fullStr | Informative noncompliance in endpoint trials |
title_full_unstemmed | Informative noncompliance in endpoint trials |
title_short | Informative noncompliance in endpoint trials |
title_sort | informative noncompliance in endpoint trials |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC469444/ https://www.ncbi.nlm.nih.gov/pubmed/15233844 http://dx.doi.org/10.1186/1468-6708-5-5 |
work_keys_str_mv | AT snapinnstevenm informativenoncomplianceinendpointtrials AT jiangqi informativenoncomplianceinendpointtrials AT iglewiczboris informativenoncomplianceinendpointtrials |