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Bayesian statistical analysis in a phase II dose-finding trial with survival endpoint in patients with B-cell chronic lymphocytic leukemia

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TitleInfo
Title
Bayesian statistical analysis in a phase II dose-finding trial with survival endpoint in patients with B-cell chronic lymphocytic leukemia
Name (type = personal)
NamePart (type = family)
Li
NamePart (type = given)
Shiansong
NamePart (type = date)
1966-
DisplayForm
Shiansong Li
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Shih
NamePart (type = given)
Weichung Joe
DisplayForm
Weichung Joe Shih
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Kim
NamePart (type = given)
Sinae
DisplayForm
Sinae Kim
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Echeverria
NamePart (type = given)
Sandra
DisplayForm
Sandra Echeverria
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Luo
NamePart (type = given)
Xiaolong
DisplayForm
Xiaolong Luo
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Public Health
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2014
DateOther (qualifier = exact); (type = degree)
2014-05
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Bayesian approaches have been widely used in designing, monitoring and analyzing clinical studies in recent years. We utilize Bayesian parametric and non-parametric statistical methods in interim monitoring and decision-making for a phase II dose-finding trial with survival endpoint. The objective of the clinical trial is to find an optimal treatment schedule at the end of the study for planning future studies, using Bayesian decision rules. The primary efficacy outcome is time to progression. Binomial-Beta model and Exponential-Gamma model are included in parametric methods. Non-parametric methods include Bayesian life-table, Beta process model, Dirichlet process model and Gibbs sampling. Simulations are conducted for each of the statistical methods under 9 different scenarios including truncated exponential entry time, and the probability of a treatment-schedule being chosen is calculated based on 1,000 simulation studies. Finally, these different statistical methods are used to find optimal treatment-schedule among 3 arms in the phase II CLL clinical trial using the most recent unblinded data.
Subject (authority = RUETD)
Topic
Public Health
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_5383
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
x, 155 p. : ill.
Note (type = degree)
Dr.P.H.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Shiansong Li
Subject (authority = ETD-LCSH)
Topic
Bayesian statistical decision theory
Subject (authority = ETD-LCSH)
Topic
Lymphocytic leukemia--Treatment
Subject (authority = ETD-LCSH)
Topic
Pharmaceutical arithmetic
RelatedItem (type = host)
TitleInfo
Title
School of Public Health ETD Collection
Identifier (type = local)
rucore10007500001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3NC5ZF3
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Li
GivenName
Shiansong
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2014-04-04 12:44:50
AssociatedEntity
Name
Shiansong Li
Role
Copyright holder
Affiliation
Rutgers University. School of Public Health
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
RightsEvent
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2014-05-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2015-05-31
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after May 31st, 2015.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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