About: Two Stage Designs for Phase III Clinical Trials

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Two Stage Designs for Phase III Clinical Trials
Creator	Follmann, Dean Proschan, Michael
Source	MedRxiv; Medline; PMC
abstract	Phase III platform trials are increasingly used to evaluate a sequence of treatments for a specific disease. Traditional approaches to structure such trials tend to focus on the sequential questions rather than the performance of the entire enterprise. We consider two-stage trials where an early evaluation is used to determine whether to continue with an individual study. To evaluate performance, we use the ratio of expected wins (RW), that is, the expected number of reported efficacious treatments using a two-stage approach compared to that using standard phase III trials. We approximate the test statistics during the course of a single trial using Brownian Motion and determine the optimal stage 1 time and type I error rate to maximize RW for fixed power. At times, a surrogate or intermediate endpoint may provide a quicker read on potential efficacy than use of the primary endpoint at stage 1. We generalize our approach to the surrogate endpoint setting and show improved performance, provided a good quality and powerful surrogate is available. We apply our methods to the design of a platform trial to evaluate treatments for COVID-19 disease.
has issue date	2020-07-31(xsd:dateTime)
bibo:doi	10.1101/2020.07.29.20164525
bibo:pmid	32793927
has license	cc0
sha1sum (hex)	5f41d5e75451d4b86cdad75565becb316ce64fcd
schema:url	https://doi.org/10.1101/2020.07.29.20164525
resource representing a document's title	Two Stage Designs for Phase III Clinical Trials
has PubMed Central identifier	PMC7418751
has PubMed identifier	32793927
schema:publication	medRxiv
resource representing a document's body	covid:5f41d5e75451d4b86cdad75565becb316ce64fcd#body_text
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