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Sharing some interim data in trial monitoring can mislead or unmask trial investigators: A scenario-based survey of trial experts

BACKGROUND: Sharing masked interim results by the Data Safety Monitoring Board (DSMB) with non-DSMB members is an important issue that can affect trial integrity. Our survey's objective is to collect evidence to understand how seemingly masked interim results or result extrapolations are interp...

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Autores principales: Borg Debono, Victoria, Mbuagbaw, Lawrence, Paul, James, Buckley, Norm, Thabane, Lehana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898486/
https://www.ncbi.nlm.nih.gov/pubmed/29696172
http://dx.doi.org/10.1016/j.conctc.2017.05.005
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author Borg Debono, Victoria
Mbuagbaw, Lawrence
Paul, James
Buckley, Norm
Thabane, Lehana
author_facet Borg Debono, Victoria
Mbuagbaw, Lawrence
Paul, James
Buckley, Norm
Thabane, Lehana
author_sort Borg Debono, Victoria
collection PubMed
description BACKGROUND: Sharing masked interim results by the Data Safety Monitoring Board (DSMB) with non-DSMB members is an important issue that can affect trial integrity. Our survey's objective is to collect evidence to understand how seemingly masked interim results or result extrapolations are interpreted and discuss whether these results should be shared at interim. METHODS: Conducted a 6 scenario-question survey asking trial experts how they interpreted three kinds of seemingly masked interim results or result extrapolation measures (interim combined event rate, adaptive conditional power and “unconditional” conditional power). RESULTS: Thirty-one current Consolidated Standards of Reporting Trials group affiliates were invited for survey participation (February 2015). Response rate: 71.0% (22/31). About half, 52.6% (95% CI: 28.9%–74.0%), (10/19), correctly indicated that the interim combined event rate can be interpreted in three ways (drug X doing better than placebo, worse than placebo or the same) if shared at interim. The majority, 72.2% (95% CI: 46.5%–89.7%), (13/18), correctly indicated that the adaptive conditional power suggests relative treatment group effects. The majority, 53.3% (95% CI: 26.6%–77.0%), (8/15), incorrectly indicated that the “unconditional” conditional power suggests relative treatment group effects. DISCUSSION/CONCLUSION: Knowledge of these three results or result extrapolation measures should not be shared outside of the DSMB at interim as they may mislead or unmask interim results, potentially introducing trial bias. For example, the interim combined event rate can be interpreted in one of three ways potentially leading to mistaken guesswork about interim results. Knowledge of the adaptive conditional power by non-DSMB members is telling of relative treatment effects thus unmasking of interim results.
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spelling pubmed-58984862018-04-25 Sharing some interim data in trial monitoring can mislead or unmask trial investigators: A scenario-based survey of trial experts Borg Debono, Victoria Mbuagbaw, Lawrence Paul, James Buckley, Norm Thabane, Lehana Contemp Clin Trials Commun Article BACKGROUND: Sharing masked interim results by the Data Safety Monitoring Board (DSMB) with non-DSMB members is an important issue that can affect trial integrity. Our survey's objective is to collect evidence to understand how seemingly masked interim results or result extrapolations are interpreted and discuss whether these results should be shared at interim. METHODS: Conducted a 6 scenario-question survey asking trial experts how they interpreted three kinds of seemingly masked interim results or result extrapolation measures (interim combined event rate, adaptive conditional power and “unconditional” conditional power). RESULTS: Thirty-one current Consolidated Standards of Reporting Trials group affiliates were invited for survey participation (February 2015). Response rate: 71.0% (22/31). About half, 52.6% (95% CI: 28.9%–74.0%), (10/19), correctly indicated that the interim combined event rate can be interpreted in three ways (drug X doing better than placebo, worse than placebo or the same) if shared at interim. The majority, 72.2% (95% CI: 46.5%–89.7%), (13/18), correctly indicated that the adaptive conditional power suggests relative treatment group effects. The majority, 53.3% (95% CI: 26.6%–77.0%), (8/15), incorrectly indicated that the “unconditional” conditional power suggests relative treatment group effects. DISCUSSION/CONCLUSION: Knowledge of these three results or result extrapolation measures should not be shared outside of the DSMB at interim as they may mislead or unmask interim results, potentially introducing trial bias. For example, the interim combined event rate can be interpreted in one of three ways potentially leading to mistaken guesswork about interim results. Knowledge of the adaptive conditional power by non-DSMB members is telling of relative treatment effects thus unmasking of interim results. Elsevier 2017-05-19 /pmc/articles/PMC5898486/ /pubmed/29696172 http://dx.doi.org/10.1016/j.conctc.2017.05.005 Text en Crown Copyright © 2017 Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Borg Debono, Victoria
Mbuagbaw, Lawrence
Paul, James
Buckley, Norm
Thabane, Lehana
Sharing some interim data in trial monitoring can mislead or unmask trial investigators: A scenario-based survey of trial experts
title Sharing some interim data in trial monitoring can mislead or unmask trial investigators: A scenario-based survey of trial experts
title_full Sharing some interim data in trial monitoring can mislead or unmask trial investigators: A scenario-based survey of trial experts
title_fullStr Sharing some interim data in trial monitoring can mislead or unmask trial investigators: A scenario-based survey of trial experts
title_full_unstemmed Sharing some interim data in trial monitoring can mislead or unmask trial investigators: A scenario-based survey of trial experts
title_short Sharing some interim data in trial monitoring can mislead or unmask trial investigators: A scenario-based survey of trial experts
title_sort sharing some interim data in trial monitoring can mislead or unmask trial investigators: a scenario-based survey of trial experts
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898486/
https://www.ncbi.nlm.nih.gov/pubmed/29696172
http://dx.doi.org/10.1016/j.conctc.2017.05.005
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