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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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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. |
format | Online Article Text |
id | pubmed-5745896 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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