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The Value of the Information That Can Be Generated: Optimizing Study Design to Enable the Study of Treatments Addressing an Unmet Need for Rare Pathogens

In traditional phase 3 trials confirming safety and efficacy of new treatments relative to a comparator, a 1-sided type I error rate of 2.5% is traditionally used and typically leads to minimum sizes of 300–600 subjects per study. However, for rare pathogens, it may be necessary to work with data fr...

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Autores principales: Dane, Aaron, Rex, John H, Newell, Paul, Stallard, Nigel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290570/
https://www.ncbi.nlm.nih.gov/pubmed/35854983
http://dx.doi.org/10.1093/ofid/ofac266
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author Dane, Aaron
Rex, John H
Newell, Paul
Stallard, Nigel
author_facet Dane, Aaron
Rex, John H
Newell, Paul
Stallard, Nigel
author_sort Dane, Aaron
collection PubMed
description In traditional phase 3 trials confirming safety and efficacy of new treatments relative to a comparator, a 1-sided type I error rate of 2.5% is traditionally used and typically leads to minimum sizes of 300–600 subjects per study. However, for rare pathogens, it may be necessary to work with data from as few as 50–100 subjects. For areas with a high unmet need, there is a balance between traditional type I error and power and enabling feasible studies. In such cases, an alternative 1-sided alpha level of 5% or 10% should be considered, and we review herein the implications of such approaches. Resolving this question requires engagement of patients, the medical community, regulatory agencies, and trial sponsors.
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spelling pubmed-92905702022-07-18 The Value of the Information That Can Be Generated: Optimizing Study Design to Enable the Study of Treatments Addressing an Unmet Need for Rare Pathogens Dane, Aaron Rex, John H Newell, Paul Stallard, Nigel Open Forum Infect Dis Review Article In traditional phase 3 trials confirming safety and efficacy of new treatments relative to a comparator, a 1-sided type I error rate of 2.5% is traditionally used and typically leads to minimum sizes of 300–600 subjects per study. However, for rare pathogens, it may be necessary to work with data from as few as 50–100 subjects. For areas with a high unmet need, there is a balance between traditional type I error and power and enabling feasible studies. In such cases, an alternative 1-sided alpha level of 5% or 10% should be considered, and we review herein the implications of such approaches. Resolving this question requires engagement of patients, the medical community, regulatory agencies, and trial sponsors. Oxford University Press 2022-05-27 /pmc/articles/PMC9290570/ /pubmed/35854983 http://dx.doi.org/10.1093/ofid/ofac266 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Review Article
Dane, Aaron
Rex, John H
Newell, Paul
Stallard, Nigel
The Value of the Information That Can Be Generated: Optimizing Study Design to Enable the Study of Treatments Addressing an Unmet Need for Rare Pathogens
title The Value of the Information That Can Be Generated: Optimizing Study Design to Enable the Study of Treatments Addressing an Unmet Need for Rare Pathogens
title_full The Value of the Information That Can Be Generated: Optimizing Study Design to Enable the Study of Treatments Addressing an Unmet Need for Rare Pathogens
title_fullStr The Value of the Information That Can Be Generated: Optimizing Study Design to Enable the Study of Treatments Addressing an Unmet Need for Rare Pathogens
title_full_unstemmed The Value of the Information That Can Be Generated: Optimizing Study Design to Enable the Study of Treatments Addressing an Unmet Need for Rare Pathogens
title_short The Value of the Information That Can Be Generated: Optimizing Study Design to Enable the Study of Treatments Addressing an Unmet Need for Rare Pathogens
title_sort value of the information that can be generated: optimizing study design to enable the study of treatments addressing an unmet need for rare pathogens
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290570/
https://www.ncbi.nlm.nih.gov/pubmed/35854983
http://dx.doi.org/10.1093/ofid/ofac266
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