About: GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic
Creator	Horby, Peter Whitehead, John
source	Medline; PMC
abstract	BACKGROUND: Conducting clinical trials to assess experimental treatments for potentially pandemic infectious diseases is challenging. Since many outbreaks of infectious diseases last only six to eight weeks, there is a need for trial designs that can be implemented rapidly in the face of uncertainty. Outbreaks are sudden and unpredictable and so it is essential that as much planning as possible takes place in advance. Statistical aspects of such trial designs should be evaluated and discussed in readiness for implementation. METHODOLOGY/PRINCIPAL FINDINGS: This paper proposes a generic ordinal sequential trial design (GOST) for a randomised clinical trial comparing an experimental treatment for an emerging infectious disease with standard care. The design is intended as an off-the-shelf, ready-to-use robust and flexible option. The primary endpoint is a categorisation of patient outcome according to an ordinal scale. A sequential approach is adopted, stopping as soon as it is clear that the experimental treatment has an advantage or that sufficient advantage is unlikely to be detected. The properties of the design are evaluated using large-sample theory and verified for moderate sized samples using simulation. The trial is powered to detect a generic clinically relevant difference: namely an odds ratio of 2 for better rather than worse outcomes. Total sample sizes (across both treatments) of between 150 and 300 patients prove to be adequate in many cases, but the precise value depends on both the magnitude of the treatment advantage and the nature of the ordinal scale. An advantage of the approach is that any erroneous assumptions made at the design stage about the proportion of patients falling into each outcome category have little effect on the error probabilities of the study, although they can lead to inaccurate forecasts of sample size. CONCLUSIONS/SIGNIFICANCE: It is important and feasible to pre-determine many of the statistical aspects of an efficient trial design in advance of a disease outbreak. The design can then be tailored to the specific disease under study once its nature is better understood.
has issue date	2017-03-09(xsd:dateTime)
bibo:doi	10.1371/journal.pntd.0005439
bibo:pmid	28278301
has license	cc-by
sha1sum (hex)	ab2e4c7ae023d55fde4ae3df32825484d00fcb3f
schema:url	https://doi.org/10.1371/journal.pntd.0005439
resource representing a document's title	GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic
has PubMed Central identifier	PMC5360336
has PubMed identifier	28278301
schema:publication	PLoS Negl Trop Dis
resource representing a document's body	covid:ab2e4c7ae023d55fde4ae3df32825484d00fcb3f#body_text
is schema:about of	named entity 'TRIAL DESIGN' named entity 'rapidly' named entity 'weeks' named entity 'unpredictable' named entity 'essential' »more»

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