Cargando…
Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times
In trials with binary outcomes, assessed repeatedly at pre-specified times and where the subject is considered to have experienced a failure at the first occurrence of the outcome, interim analyses are performed, generally, after half or more of the subjects have completed follow-up. Depending on th...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4087327/ https://www.ncbi.nlm.nih.gov/pubmed/25019050 http://dx.doi.org/10.1186/2193-1801-3-323 |
_version_ | 1782324914373525504 |
---|---|
author | Parpia, Sameer Julian, Jim A Gu, Chushu Thabane, Lehana Levine, Mark N |
author_facet | Parpia, Sameer Julian, Jim A Gu, Chushu Thabane, Lehana Levine, Mark N |
author_sort | Parpia, Sameer |
collection | PubMed |
description | In trials with binary outcomes, assessed repeatedly at pre-specified times and where the subject is considered to have experienced a failure at the first occurrence of the outcome, interim analyses are performed, generally, after half or more of the subjects have completed follow-up. Depending on the duration of accrual relative to the length of follow-up, this may be inefficient, since there is a possibility that the trial will have completed accrual prior to the interim analysis. An alternative is to plan the interim analysis after subjects have completed follow-up to a time that is less than the fixed full follow-up duration. Using simulations, we evaluated three methods to estimate the event proportion for the interim analysis in terms of type I and II errors and the probability of early stopping. We considered: 1) estimation of the event proportion based on subjects who have been followed for a pre-specified time (less than the full follow-up duration) or who experienced the outcome; 2) estimation of the event proportion based on data from all subjects that have been randomized by the time of the interim analysis; and 3) the Kaplan-Meier approach to estimate the event proportion at the time of the interim analysis. Our results show that all methods preserve and have comparable type I and II errors in certain scenarios. In these cases, we recommend using the Kaplan-Meier method because it incorporates all the available data and has greater probability of early stopping when the treatment effect exists. |
format | Online Article Text |
id | pubmed-4087327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-40873272014-07-11 Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times Parpia, Sameer Julian, Jim A Gu, Chushu Thabane, Lehana Levine, Mark N Springerplus Research In trials with binary outcomes, assessed repeatedly at pre-specified times and where the subject is considered to have experienced a failure at the first occurrence of the outcome, interim analyses are performed, generally, after half or more of the subjects have completed follow-up. Depending on the duration of accrual relative to the length of follow-up, this may be inefficient, since there is a possibility that the trial will have completed accrual prior to the interim analysis. An alternative is to plan the interim analysis after subjects have completed follow-up to a time that is less than the fixed full follow-up duration. Using simulations, we evaluated three methods to estimate the event proportion for the interim analysis in terms of type I and II errors and the probability of early stopping. We considered: 1) estimation of the event proportion based on subjects who have been followed for a pre-specified time (less than the full follow-up duration) or who experienced the outcome; 2) estimation of the event proportion based on data from all subjects that have been randomized by the time of the interim analysis; and 3) the Kaplan-Meier approach to estimate the event proportion at the time of the interim analysis. Our results show that all methods preserve and have comparable type I and II errors in certain scenarios. In these cases, we recommend using the Kaplan-Meier method because it incorporates all the available data and has greater probability of early stopping when the treatment effect exists. Springer International Publishing 2014-06-26 /pmc/articles/PMC4087327/ /pubmed/25019050 http://dx.doi.org/10.1186/2193-1801-3-323 Text en © Parpia et al.; licensee Springer. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. |
spellingShingle | Research Parpia, Sameer Julian, Jim A Gu, Chushu Thabane, Lehana Levine, Mark N Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times |
title | Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times |
title_full | Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times |
title_fullStr | Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times |
title_full_unstemmed | Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times |
title_short | Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times |
title_sort | interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4087327/ https://www.ncbi.nlm.nih.gov/pubmed/25019050 http://dx.doi.org/10.1186/2193-1801-3-323 |
work_keys_str_mv | AT parpiasameer interimanalysisforbinaryoutcometrialswithalongfixedfollowuptimeandrepeatedoutcomeassessmentsatprespecifiedtimes AT julianjima interimanalysisforbinaryoutcometrialswithalongfixedfollowuptimeandrepeatedoutcomeassessmentsatprespecifiedtimes AT guchushu interimanalysisforbinaryoutcometrialswithalongfixedfollowuptimeandrepeatedoutcomeassessmentsatprespecifiedtimes AT thabanelehana interimanalysisforbinaryoutcometrialswithalongfixedfollowuptimeandrepeatedoutcomeassessmentsatprespecifiedtimes AT levinemarkn interimanalysisforbinaryoutcometrialswithalongfixedfollowuptimeandrepeatedoutcomeassessmentsatprespecifiedtimes |