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Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review

OBJECTIVE: The use of minimum clinically important difference in the hypothesis formulation for superiority trials is similar in principle to the concept of non-inferiority or equivalence trial. However, most clinical trials are analysed testing zero clinical difference. Since the minimum clinically...

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Autores principales: Bigirumurame, Theophile, Kasim, Adetayo S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5745896/
https://www.ncbi.nlm.nih.gov/pubmed/29282120
http://dx.doi.org/10.1186/s13104-017-3117-4
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author Bigirumurame, Theophile
Kasim, Adetayo S.
author_facet Bigirumurame, Theophile
Kasim, Adetayo S.
author_sort Bigirumurame, Theophile
collection PubMed
description OBJECTIVE: The use of minimum clinically important difference in the hypothesis formulation for superiority trials is similar in principle to the concept of non-inferiority or equivalence trial. However, most clinical trials are analysed testing zero clinical difference. Since the minimum clinically important difference is pre-defined for power calculation, it is important to incorporate it in both the hypothesis testing and the interpretation of findings from clinical trials. RESULTS: We reviewed a set of 50 publications (25 with binary outcome, and 25 with survival time outcome). 20% of the 50 published trials that were statistically significant, were also clinically significant based on the minimum clinically important risk differences (or hazard ratio) used for their power calculations. This snap review seems to suggest that most published trials with statistically significant results were less likely to be clinically significant, which may partly explain the high false positive findings associated with findings from superiority trials. Furthermore, none of the reviewed publications explicitly used minimum clinically important difference in the interpretation of their findings. However, a systematic review is needed to critically appraise the impact of the current practice on false positive rate in published trials with significant findings.
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spelling pubmed-57458962018-01-03 Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review Bigirumurame, Theophile Kasim, Adetayo S. BMC Res Notes Research Note OBJECTIVE: The use of minimum clinically important difference in the hypothesis formulation for superiority trials is similar in principle to the concept of non-inferiority or equivalence trial. However, most clinical trials are analysed testing zero clinical difference. Since the minimum clinically important difference is pre-defined for power calculation, it is important to incorporate it in both the hypothesis testing and the interpretation of findings from clinical trials. RESULTS: We reviewed a set of 50 publications (25 with binary outcome, and 25 with survival time outcome). 20% of the 50 published trials that were statistically significant, were also clinically significant based on the minimum clinically important risk differences (or hazard ratio) used for their power calculations. This snap review seems to suggest that most published trials with statistically significant results were less likely to be clinically significant, which may partly explain the high false positive findings associated with findings from superiority trials. Furthermore, none of the reviewed publications explicitly used minimum clinically important difference in the interpretation of their findings. However, a systematic review is needed to critically appraise the impact of the current practice on false positive rate in published trials with significant findings. BioMed Central 2017-12-28 /pmc/articles/PMC5745896/ /pubmed/29282120 http://dx.doi.org/10.1186/s13104-017-3117-4 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Note
Bigirumurame, Theophile
Kasim, Adetayo S.
Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review
title Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review
title_full Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review
title_fullStr Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review
title_full_unstemmed Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review
title_short Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review
title_sort can testing clinical significance reduce false positive rates in randomized controlled trials? a snap review
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5745896/
https://www.ncbi.nlm.nih.gov/pubmed/29282120
http://dx.doi.org/10.1186/s13104-017-3117-4
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