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Predicting clinical trial results based on announcements of interim analyses

BACKGROUND: Announcements of interim analyses of a clinical trial convey information about the results beyond the trial’s Data Safety Monitoring Board (DSMB). The amount of information conveyed may be minimal, but the fact that none of the trial’s stopping boundaries has been crossed implies that th...

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Autores principales: Broglio, Kristine R, Stivers, David N, Berry, Donald A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973959/
https://www.ncbi.nlm.nih.gov/pubmed/24607270
http://dx.doi.org/10.1186/1745-6215-15-73
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author Broglio, Kristine R
Stivers, David N
Berry, Donald A
author_facet Broglio, Kristine R
Stivers, David N
Berry, Donald A
author_sort Broglio, Kristine R
collection PubMed
description BACKGROUND: Announcements of interim analyses of a clinical trial convey information about the results beyond the trial’s Data Safety Monitoring Board (DSMB). The amount of information conveyed may be minimal, but the fact that none of the trial’s stopping boundaries has been crossed implies that the experimental therapy is neither extremely effective nor hopeless. Predicting success of the ongoing trial is of interest to the trial’s sponsor, the medical community, pharmaceutical companies, and investors. We determine the probability of trial success by quantifying only the publicly available information from interim analyses of an ongoing trial. We illustrate our method in the context of the National Surgical Adjuvant Breast and Bowel (NSABP) trial, C-08. METHODS: We simulated trials based on the specifics of the NSABP C-08 protocol that were publicly available. We quantified the uncertainty around the treatment effect using prior weights for the various possibilities in light of other colon cancer studies and other studies of the investigational agent, bevacizumab. We considered alternative prior distributions. RESULTS: Subsequent to the trial’s third interim analysis, our predictive probabilities were: that the trial would eventually be successful, 48.0%; would stop for futility, 7.4%; and would continue to completion without statistical significance, 44.5%. The actual trial continued to completion without statistical significance. CONCLUSIONS: Announcements of interim analyses provide information outside the DSMB’s sphere of confidentiality. This information is potentially helpful to clinical trial prognosticators. ‘Information leakage’ from standard interim analyses such as in NSABP C-08 is conventionally viewed as acceptable even though it may be quite revealing. Whether leakage from more aggressive types of adaptations is acceptable should be assessed at the design stage.
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spelling pubmed-39739592014-04-04 Predicting clinical trial results based on announcements of interim analyses Broglio, Kristine R Stivers, David N Berry, Donald A Trials Research BACKGROUND: Announcements of interim analyses of a clinical trial convey information about the results beyond the trial’s Data Safety Monitoring Board (DSMB). The amount of information conveyed may be minimal, but the fact that none of the trial’s stopping boundaries has been crossed implies that the experimental therapy is neither extremely effective nor hopeless. Predicting success of the ongoing trial is of interest to the trial’s sponsor, the medical community, pharmaceutical companies, and investors. We determine the probability of trial success by quantifying only the publicly available information from interim analyses of an ongoing trial. We illustrate our method in the context of the National Surgical Adjuvant Breast and Bowel (NSABP) trial, C-08. METHODS: We simulated trials based on the specifics of the NSABP C-08 protocol that were publicly available. We quantified the uncertainty around the treatment effect using prior weights for the various possibilities in light of other colon cancer studies and other studies of the investigational agent, bevacizumab. We considered alternative prior distributions. RESULTS: Subsequent to the trial’s third interim analysis, our predictive probabilities were: that the trial would eventually be successful, 48.0%; would stop for futility, 7.4%; and would continue to completion without statistical significance, 44.5%. The actual trial continued to completion without statistical significance. CONCLUSIONS: Announcements of interim analyses provide information outside the DSMB’s sphere of confidentiality. This information is potentially helpful to clinical trial prognosticators. ‘Information leakage’ from standard interim analyses such as in NSABP C-08 is conventionally viewed as acceptable even though it may be quite revealing. Whether leakage from more aggressive types of adaptations is acceptable should be assessed at the design stage. BioMed Central 2014-03-07 /pmc/articles/PMC3973959/ /pubmed/24607270 http://dx.doi.org/10.1186/1745-6215-15-73 Text en Copyright © 2014 Broglio et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Broglio, Kristine R
Stivers, David N
Berry, Donald A
Predicting clinical trial results based on announcements of interim analyses
title Predicting clinical trial results based on announcements of interim analyses
title_full Predicting clinical trial results based on announcements of interim analyses
title_fullStr Predicting clinical trial results based on announcements of interim analyses
title_full_unstemmed Predicting clinical trial results based on announcements of interim analyses
title_short Predicting clinical trial results based on announcements of interim analyses
title_sort predicting clinical trial results based on announcements of interim analyses
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973959/
https://www.ncbi.nlm.nih.gov/pubmed/24607270
http://dx.doi.org/10.1186/1745-6215-15-73
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